bluuebunny/crossref_metadata_2025 huggingface dataset:
Absence of Tils in Biopsy is Associated with Worse Progression Free Survival in Early Stage Melanoma
Authors:   University of Florida College of Medicine, USA., McGrath Kyle , Elliott Tyler ,   University of Florida College of Medicine, USA., Archibald Vincent ,   University of Florida College of Medicine, USA., Matich Erica ,   University of Florida College of Medicine, USA., Galochkina Zhanna ,   Division of Quantitative Sciences, University of Florida Health Cancer Center, USA., Lee Ji-Hyun ,   Division of Quantitative Sciences, University of Florida Health Cancer Center, USA., Doonan Bently ,   Lillian S Wells Department of Neurosurgery, University of Florida, Preston A Wells, Jr Center for Brain Tumor Therapy, USA.
Published: May 2024

Background: Recent data suggest that a subset of early stage melanoma patients may benefit from adjuvant immunotherapy. Objective: To identify findings in biopsy or surgical pathology reports associated with poor prognosis in patients diagnosed with stage I and II cutaneous melanoma. Methods: This was a retrospective cohort study of 68 stage I and II cutaneous melanoma patients treated at our institution from 2010 to 2022. Inclusion criteria were patients with stage I or II melanoma with both a biopsy and surgical pathology report. The primary outcome of the study was the prognostic value of biopsy findings on progression free survival (PFS). KaplanMeier and Cox-proportional hazards models were used to evaluate risk factors for progression. Results: Patients with ulceration on biopsy had a 16.1x greater risk of progression than those without ulceration [HR 16.1, 95% CI: 2.60-99.5]. Patients with absent lymphocytes on biopsy had a 9.5x greater risk of progressing compared to those with lymphocytes present [HR 9.45, 95% CI: 1.99-44.8]. Ulceration or absent TILs were associated with significantly worse PFS. Conclusions: Ulceration and absence of TILs on biopsy are associated with increased risk of progression in stage I and II melanoma patients.
Primary Retroperitoneal Mature Cystic Teratoma (Dermoid Cyst) in Pelvic Musculature
Authors:   University of Oklahoma Health Sciences Center, USA., Fisher Hailey N , Ramseyer Timothy G ,   University of Oklahoma Health Sciences Center, USA., Eriksson Zane ,   University of Oklahoma Health Sciences Center, USA., McBride Jeffrey D ,   University of Oklahoma Health Sciences Center, USA., Asadbeigi Sepideh N ,   University of Oklahoma Health Sciences Center, USA.
Published: May 2024

Dermoid cysts, or mature cystic teratomas containing ectoderm-derived skin adnexa, rarely occur intramuscularly, especially within the male pelvic musculature. We present a male patient with a dermoid cyst within the obturator internus spreading into the adductor compartment and the pelvic cavity. In contrast to dermoid cysts in previous reports, the cyst appeared centered in muscle rather than simply perforating muscle via an extension. The case is also notable for the rapid recurrence of the cyst after incomplete resection and intraoperative rupture
Cost Monitoring and Management Algorithms in the Construction Process of Building Projects
Authors: Yang Liu
Published: May 2024

Construction project cost estimation is an essential activity in construction-based fields; it offers a valuable source for the project feasibility studies and the design plan comparisons, and the accuracy can directly influence project investment decisions. A successful implementation of project cost forecasts makes it easier to control and manage project costs. Therefore, this paper presents the Ladybug Reptile Search Algorithm_ Deep Maxout Network (LRSA_DMN) (LRSA_DMN) to estimate construction costs. Additionally, LRSA is included to correct DMN weights. Furthermore, Bootstrap scheme is used to augment data and use this data to input the DMN for cost estimation. In addition, features are selected using a Weighted Correlation Coefficient to choose the best features for further processing. The test results show that LRSA_DMN performs better regarding MSE, RMSE, and Accuracy by 0.092, 0.371, and 0.907, respectively
Construction of Sports Music Integration Training and Performance Practice System Based on Virtual Reality Technology
Authors: Dapeng Yang
Published: May 2024

The development of a virtual reality-based system that incorporates audio into physical routines presents an innovative approach to games performance and training practice. By leveraging virtual reality technology, athletes are immersed in simulated environments where they can engage in synchronized movements with musical accompaniment, enhancing their overall performance and training experience. The system provides customizable training sessions tailored to individual athlete needs, allowing for real-time feedback and performance analysis. Through the integration of music, athletes are able to synchronize their movements with rhythmic cues, fostering better coordination, timing, and rhythm in their athletic routines. The virtual reality environment offers a highly immersive experience, replicating real-world training scenarios and allowing athletes to visualize and practice their routines in a dynamic and interactive setting. Additionally, the system incorporates performance metrics and analytics to track progress over time, enabling athletes to monitor their development and make adjustments to their training regimen as needed. Ultimately, by utilizing virtual reality technology and music synchronization, the development of this sports music integration training and performance practice system represents a cutting-edge method of athletic training. By providing athletes with a highly immersive and customizable training experience, this system has the potential to enhance athletic performance, improve training outcomes, and revolutionize the way athletes train and prepare for competition.
Numerical Simulation of Motion Test of Bionic Amphibious Quadruped Robot
Authors: Jie Zhao
Published: May 2024

Bionic amphibious quadruped robots are a huge leap in robotics, with the ability to navigate various terrains with agility and efficiency. In this study, the researchers utilized numerical simulations of motion tests to assess the locomotion skills of these extraordinary robotic systems. They learned a lot about their functioning and problems by rigorously analyzing performance parameters across various terrains and conditions, such as terrain adaptability, traversal speed, energy efficiency, stability, and manoeuvrability. The results they obtained highlighted the importance of adaptive control algorithms and mechanical designs in maximizing traversal speed and energy economy, especially while negotiating difficult terrains. In addition, the study demonstrated the interdisciplinary character of research in bionic amphibious quadruped robots, drawing on insights from biomechanics, control theory, robotics, and computational modelling. By combining previous research and utilizing computational simulation approaches, they opened the road for the creation of versatile and durable robotic systems capable of navigating difficult terrains and surroundings with precision and efficiency. Future research efforts could focus on improving design and control, investigating novel propulsion mechanisms, adaptive locomotion tactics, and biomimetic control algorithms to improve performance and adaptability. Addressing the challenges identified in the research and seizing opportunities for innovation will drive the development of robotic systems that push the limits of locomotion capabilities and open up new possibilities for applications in exploration, search and rescue, environmental monitoring, and beyond.
Toward Digital Hospital Services: Developing an Integrated Model to Understand Patient Intentions for Utilizing Online Hospital Service Platforms
Authors: Peng Qin
Published: May 2024

In view of the low user acceptance rate of online medical, this study aims to explores the factors affecting users’ intention to use online hospital service platform (OHP) based on the unified theory of acceptance and use of technology (UTAUT) and the health belief model (HBM). This study adopts a quantitative research method, collects 440 valid responses from Sichuan province by convenience sampling. The reliability and validity analysis are conducted by SPSS and AMOS, and the proposed research hypotheses are verified by structural equation model. The results uncovers facilitating condition, performance expectancy, effort expectancy, perceived susceptibility and perceived severity significantly positively affect users’ intention to use OHP. Furthermore, this study constructs a integrated model to encourage the users to accept the online hospital service platform, hence enhancing the accessibility and efficacy of healthcare services in a digital landscape.
Improved Adaptive Network-Based Fuzzy Inference System Approach for Power Flow Analysis in Interconnected DC Microgrid
Authors: K Saravanan
Published: May 2024

High-performance power conversion needs are becoming more and more important for microgrid applications. In actuality, many contemporary DC distribution systems use isolated bidirectional dc-dc converters. Hence, in this paper, an Improved Adaptive Network-based Fuzzy Inference System (IANFIS)is developed to control the output power of the components and reduce the variation among the consumption and generation of the power while managing a constant DC bus voltage. This work proposes a power management control strategy that ensures the power balance of a stand-alone DC microgrid where DAB converters link the battery energy storage (BES) unit and the renewable energy source (RES). The generation side, or photovoltaic (PV) system and BES, is coupled to the storage systems and renewable energy sources. Furthermore, a DC microgrid is connected to the load demand. The load demand is compensated with the help of the storage and generation systems with the help of a dual active bridge converter. The DAB is connected with the dual DC microgrid system for managing power flow among the two DC microgrids. This dual active bridge converter is utilized to balance the power among Dual DC microgrids. The proposed methodology is developed to manage the power among generation and load demand management.  The proposed method is evaluated on a dual active bridge converter connected microgrid system with the components of PV and BESS respectively.
A Comparative Study of Khasi Speech Recognition Systems with Recurrent Neural Network-Based Language Model
Authors: S. Deepajothi
Published: May 2024

This paper offers a comparative analysis of Khasi speech recognition systems utilizing a recurrent neural network-based language model (RNN-LM). Develop different acoustic models (AMs) to evaluate the optimal performance. This paper observed that using RNN-LM performed best than traditional other models. The wave surfer performs data processing followed by collecting the recorder based continuous speech database. Moreover, a minimization of word error rate (WER) in 2.83.8% range for major speech data and 2.4-3.5% for minor speech data. Additionally, two acoustic features are used, and from the experimental results, the Mel frequency cepstral coefficient (MFCC) yielded improved performance than the perceptual linear prediction (PLP).
Challenges Related to Grammatical and Morphological Processing of Arabic Texts by Means of Artificial Intelligence
Authors: Heba Mohamed Ali Ahmed Mohamed Ali
Published: May 2024

This research aims to study the challenges facing artificial intelligence in processing Arabic texts grammatically and morphologically, by conducting a survey on a random sample of Microsoft Word 2010 users. The research provided a theoretical framework for the subject of the study, as it addressed the concept of artificial intelligence, as well as the general challenges facing artificial intelligence and some challenges specific to processing Arabic texts. The research relied on the descriptive approach, and this helped highlight the importance of the study and provide a comprehensive vision of its subject. The study concluded a set of results, the most important of which are: - There are many challenges facing users in processing Arabic texts grammatically and morphologically, such as derivation, morphology, and the breadth and comprehensiveness of the Arabic language. - The inability of artificial intelligence so far to reach a high degree of quality and efficiency in processing Arabic texts grammatically and morphologically. - The possibility of processing the Arabic language in the future by adding some software operations that help develop the machine’s capabilities to understand the Arabic language and the ability to express it effectively, through the use of new artificial intelligence methods, such as deep learning and machine learning. The study recommended a number of important recommendations, which are: - Microsoft Word is constantly updated by Microsoft, in order to ensure the quality and efficiency of the program in processing Arabic texts grammatically and morphologically. - Encouraging students and researchers to conduct more scientific research in the field of automated processing of linguistic texts, in order to enhance the progress and development of this vital field.
Optimization of English Classroom Interaction Models Incorporating Machine Learning
Authors: Ren Shiming
Published: May 2024

The optimization of English classroom interaction models incorporating machine learning represents a paradigm shift in language education, offering innovative ways to enhance student engagement, participation, and learning outcomes. With machine learning algorithms, educators can analyze various factors such as student proficiency levels, learning styles, and behavioral patterns to dynamically adapt classroom interactions in real-time. These models can predict and optimize the timing, content, and format of instructional activities, fostering more personalized and effective learning experiences.This paper explores the implementation of optimized interaction models and machine learning predictions in the English classroom to enhance student engagement, academic performance, and personalized instruction. Through the analysis of various tables and findings, key insights emerge regarding the effectiveness of student-centered learning, active learning strategies, differentiated instruction, and technology integration within the interaction model. Additionally, machine learning predictions offer valuable opportunities for personalized instruction based on predicted proficiency levels. The study demonstrates promising outcomes, but limitations such as sample size constraints and data quality issues must be addressed to ensure the reliability and applicability of the findings. Results indicate a 15% increase in student participation rates, a 12-point rise in average test scores, and a shift from high to moderate teacher intervention frequency. Additionally, machine learning predictions achieved an accuracy rate of 80%, with 8 out of 10 correct predictions. Aspect evaluation scores revealed high effectiveness in student-centered learning (9.2), formative assessment (9.3), and teacher facilitation (9.0). These findings contribute to enhancing teaching and learning practices, supporting educators in fostering more engaging and personalized learning experiences for students.
Optimization and Application of English Word Memory Algorithm Based on Reinforcement Learning
Authors: Zhang Guangyong
Published: May 2024

The optimization and application of an English word memory algorithm based on reinforcement learning involve refining a system that utilizes reinforcement learning techniques to enhance vocabulary retention. By leveraging reinforcement learning, the algorithm can adapt its strategies for presenting and reviewing English words based on users' responses and performance. This adaptive approach enables personalized and effective learning experiences, wherein the algorithm adjusts the frequency and timing of word repetitions to maximize memorization efficiency. Applications of this optimized algorithm span language learning platforms, educational apps, and personalized tutoring systems, offering learners tailored support to strengthen their English vocabulary acquisition and retention skills. This paper introduces the Spider Swarm Optimized English Word Memory Algorithm (SSOEWMA) algorithm, a novel approach aimed at optimizing language processing and learning tasks. Leveraging principles of reinforcement learning and swarm intelligence, SSOEWMA demonstrates its effectiveness in enhancing various aspects of language processing, including word difficulty assessment, sentence estimation, memory retention, and student performance evaluation. Through a series of experiments and evaluations, we showcase SSOEWMA ability to optimize dataset attributes, accurately estimate sentence characteristics, and improve memory retention performance. Simulation results achieved an average word recall accuracy of 85% across multiple evaluations. Through its utilization of reinforcement learning principles and swarm intelligence, SSOEWMA significantly improved memory retention performance, reducing recall latency by an average of 20% compared to baseline measures. Additionally, the algorithm demonstrated strong learning efficiency, converging to optimal solutions with a speed increase of 30% compared to traditional methods.
Hierarchical Coordinated Control Strategy for Active Power in Distribution Networks with Scaled Distributed Generation Access
Authors: Xiaoming Zhang
Published: May 2024

Promoting scaled distributed wind turbines and photovoltaic, and other distributed generations access to the distribution network is an important measure for realize the goal of carbon peaking and carbon neutrality and to build new-type power systems. However, as the installed capacity of wind turbine, photovoltaic and other intermittent renewable energy sources climbs dramatically, the security and consumption problems of the distribution network are becoming increasingly prominent, and there is an urgent requirement to improve the active power control capability of distributed generation. To optimize the operation stability and consumption economy of the distribution network, a hierarchical coordinated control strategy for active power of scaled distributed generation is proposed based on the principle of unified control and hierarchical management, including peaking control, frequency control, mesh control and market trading control, to coordinate and optimize the system operation safety and consumption economy. The proposed strategy optimizes active power control instructions in the layer of distribution network layer, mesh layer, and functional area layer, thus fully expanding the depth and breadth of the consumption for distributed generation. The effectiveness of the proposed strategy is proved by the actual operation of Liaoning power grid.
Enhancement of Power Quality through the Implementation of a Hybrid Artificial Intelligence Model within Solar-Wind Energy Systems
Authors: Rambabu.yerra
Published: May 2024

The generation of electricity is significantly assisted by hybrid solar-wind power systems, which also play a crucial role in the advancement of intelligent grids. Furthermore, the integration of wind and solar energy storage control systems, in conjunction with energy markets, has rendered the electricity grid more economically feasible. To meet the growing demand for electricity, hybrid renewable energy systems connected to microgrids consist of substantial identifying elements. The issue of harmonic distortion in microgrids arising from nonlinear loads is a fundamental area of research. Understanding the impact of microgrids on power quality is also of great importance. This study focuses on enhancing power quality in solar-wind hybrid systems by incorporating emerging Artificial Intelligence (AI) methodologies. 
The proposed approach comprises two main components: (i) detection of distortions caused by voltage fluctuations and (ii) improvement of power quality through an AI-based control system. Initially, power distortions are identified and eliminated using the Enhanced Kalman Filter (EKF) algorithm. A Hybrid Artificial Neural Network with Fuzzy Intelligence (HANFI) model is then developed based on this power data. This model integrates two prominent neural network architectures with fuzzy systems. Experimental validation of the system is conducted using MATLAB, which facilitates the simulation of hybrid energy systems.
Blockchain-Based Secure Management of Digital Credentials for Interns
Authors: Poonam Verma
Published: May 2024

Since the onset of the pandemic of COVID-19, the academic world has been making efforts to popularize micro-credentials. In medical education, medical interns would become doctors in their specific specializations. For becoming doctors, the medical interns would apply for a doctor’s license which requires the authorities to verify the credentials of the medical interns. The present paper presents a secure application deploying Blockchain to manage the micro-credentials and the specializations earned by the interns. This paper highlights the stackability of the Medical Portfolio Management System for Medical Interns. It describes an innovative approach to develop a decentralized immutable secure personal details management for organizing the digital micro-credentials earned by the Medical Interns based on their skills/specializations.  Most of the platforms have worked on the concept of the stackability of micro-credentials. The portfolio Management can request for certification, aggregation, and synchronization of Personal Profiles (MIP) in a local repository or wallet. Further, such a portfolio management network is feasible and immune to many of the vulnerabilities while sharing the credentials.
Automatic Braking System
Authors: Rakhi Pete
Published: May 2024

With the proliferation of vehicles and the integration of technology into daily transportation, ensuring road safety has become paramount. Traffic accidents, often resulting in substantial damage and casualties, persist as a global concern. The Automatic Braking System (ABS) stands as a pivotal safety innovation adopted by vehicle manufacturers worldwide. This paper explores the significance and functionality of ABS in preventing wheel lock-up during braking, thereby enabling drivers to maintain steering control. Through an examination of ABS technology, its effectiveness, limitations, and potential advancements, this research aims to contribute to the ongoing discourse on enhancing road safety measures in the modern automotive landscape.
Estimating Malware Impact on Network Traffic Analysis by Using Wireshark
Authors: Syed Shameem
Published: May 2024

With the increasing prevalence of advanced cyber threats, there is a growing need for effective cybersecurity measures that can detect and visualize malware attacks. This research introduces an integrated approach that combines malware detection techniques with geospatial visualization methods to enhance the identification and analysis of cyber-attacks. By analyzing packets in the HTTP protocol, we identify suspicious file transfers and compute their hash values for further examination. To assess the threat level of these transferred files, we utilize the Virus Total platform to conduct comprehensive scans for malware. At the same time, by utilizing geolocation data, we map out both the origins and destinations of these attacks, providing valuable spatial context for understanding global patterns in cyber threats. In addition to enabling the identification of potentially harmful files, the proposed approach also provides a comprehensive visualization of how these threats are spread geographically. Our findings contribute to advancing cybersecurity strategies by facilitating proactive threat mitigation and enhancing incident response capabilities. The integration of malware detection, hash analysis, and geospatial visualization emphasizes the importance of adopting a multidimensional approach in strengthening network security infrastructure.
Assistive Technology for Navigation of Visually Impaired People
Authors: Mohammed Fayiz Ferosh
Published: May 2024

In this paper, an assistive navigational technology was proposed for those who are blind. People who are visually impaired are more likely to be physically inactive, move more slowly, and dread falling. As a result, the majority of them lack the confidence necessary to travel on their own in strange places. Despite the fact that some technology advancements can help them, not all of them are affordable to the common man. Through our efforts, we hope to help visually impaired persons feel secure and confident while navigating new surroundings. Assistive tech- nology for navigation of visually impaired people is an affordable and efficient computer vision based blind guidance system that helps the user detect the distance to obstacles well in advance and avoid them. The suggested system also includes an emergency distress alert feature that enables users to communicate their locations in an emergency.
Enhanced Cost-sensitive Ensemble Learning for Imbalanced Class in Medical Data
Authors: M. Kavitha
Published: May 2024

The challenge of imbalanced datasets in machine learning, particularly in the medical and public health sectors, necessitates innovative solutions that enhance predictive accuracy and reduce misclassification costs. This paper introduces the Enhanced Cost Sensitive Ensemble Learning (ECSEL), a novel approach that combines cost-sensitive learning with ensemble techniques to address the imbalance inherent in many critical datasets. We evaluate ECSEL on two specific datasets: the Framingham Heart Study dataset, which is pivotal in cardiovascular disease prediction, and a dataset focused on COVID-19 infection forecasting, relevant for public health responses. The results demonstrate that ECSEL significantly outperforms traditional methods like SMOTE, D-SMOTE, and BP-SMOTE by improving accuracy, precision, recall, and ROC-AUC values, particularly reducing Type II errors in scenarios where the cost of false negatives is exceptionally high. The method’s effectiveness is showcased through its superior performance in predicting cardiovascular risks and its robustness in forecasting the spread of COVID-19, reflecting its applicability and potential in real-world settings.
A Machine Learning Approach for Detection and Classification of Colon Cancer using Convolutional Neural Network Architecture
Authors: Subrata Sinha
Published: May 2024

In both developing and developed countries, cancer has become one of the most fearsome health ailments in the 21st century. Among the different variants of cancer, colon cancer is the 3rd most prevalent cancer globally and the 2nd deadliest form of cancer. Early diagnosis is very critical for the successful treatment of colon cancer.  In recent times, machine-learning approaches have made significant strides in IoT-assisted healthcare systems. Computer-aided diagnostic systems driven by deep learning algorithms can detect colon cancer with great accuracy, assisting the medical profession in quick diagnosis and developing quick remedies against it. In our approach, we have developed a deep learning model based on convolutional neural network architecture to accurately classify and detect colon cancer.  The developed model has been trained with 10,000 histopathological images of the colon, divided into two classes: colon adenocarcinoma and colon benign tissues, each containing 5000 images. We have also employed various performance metrics in our research to monitor the performance of our machine-learning model.  The proposed model has been trained for 30 epochs with a batch size of 32 and achieved an overall accuracy of 98.79%.
Analysis of the Rendering of Deep and Short Art Effects Under the Multimedia Background Taking into Account the 3D Ink Rendering Algorithm
Authors: Zhong Lingling
Published: May 2024

People's living standard is improving and the economy is developing rapidly, so the demand for spiritual culture is also increasing. Today, with the rapid development of information technology, 3D ink rendering technology has become an indispensable part of modern art. It is not only a visual expression and tool, but also has a great impact on people's daily life. It is based on computer language and multimedia software. Its main purpose is to express art through images, sound and text; it can also integrate various complex and creative elements to form a whole picture, thus giving the whole picture a certain sense of hierarchy. This will give people an intuitive and strong visual feeling, thus achieving the purpose of "visual communication". In 3D ink rendering technology, image processing and sound effects are the two most important aspects. Among them, there is a certain correlation between digital works and text and other multimedia contexts with strong and far-reaching art effects rendering; and the impact of color and sound effects on 3D scenes should not be ignored: from the overall perspective, the sense of picture and enhanced visual effects can enhance the virtual reality space atmosphere and enrich the visual experience; but from the specific content, this may reduce the efficiency of the rendering process. In this paper, we start from the principle of ink rendering algorithm and analyze its impact on the picture effect and color processing in combination with 3D ink rendering technology.
Interactive Education with Exploration Virtual Reality Technology
Authors: Siti Hazyanti Mohd Hashim
Published: May 2024

Nowadays, technology plays a fundamental role in the development of daily life activities. In this regard, there is an increase in disciplines that have used technologies, with educational fields standing out above all. Within education, there are a series of emerging technologies that are increasingly implemented in the classroom. The use of virtual reality in education is a good way to attract them in learning. Using virtual reality in learning give positive impact to the trend of increasing motivation, more attracting and fast learning. This is to design the 3-dimensional environment for education. The usefulness of this research is Interactive Virtual reality game is new technology in education, inspire players to focus, feel interesting, and enjoy playing the game. Helpful in motivating students due to having an interactive, interesting, fantasy-occupied and challenging game. The students could improve their learning as they are well immersed in the game. Using 3-dimensional virtual reality game acts as a new way to improve a student's skill in learning. The virtual reality environment will give the students a new environment that they can feel real while wearing the Oculus and doing exercises. The virtual reality game design will be used at home.
A strukturált leletezés jelentősége az egészségügyben
Authors: Bagdy-Bálint Réka , Pálvölgyi Eszter Frida , Németh Bence , Rózsa Noémi Katinka
Published: May 2024

Napjaink digitális világa lehetőséget teremt az orvosi diagnosztikus vizsgálatok, terápiás eljárások és kutatási folyamatok rohamos fejlődésére. Az egyetemi szintű kutatótevékenység szempontjából az egyik legnagyobb innovációs jelentőséggel az adatok digitális tárolása és pontos, gyors feldolgozása bír. A strukturált, mindannyiunk számára elérhető és átlátható adattárolás azonban a legtöbb hazai és nemzetközi intézményben máig nem megoldott.
Célunk a korábbi tanulmányok alapján alátámasztani, hogy az egészségügyi ágazatban is egyre nagyobb teret nyer a modern digitális eszközök, elektronikus munkafolyamatok és az innovatív adatfeldolgozási módszerek alkalmazása. Az anamnesztikus és diagnosztikus protokollok és azok követési tendenciájának felmérései alapján szeretnénk bizonyítani, hogy a hatékonyabb betegellátó- és kutatómunka elérése érdekében célszerű az orvosi adatokat egy strukturált leletező rendszerbe felvenni.
A Pubmed/Medline adatbázisban MeSH kifejezések és szabad szöveg felhasználásával elsősorban szisztematikus áttekintő irodalmat kerestünk. Miután a szakirodalom, valamint a saját méréseink alapján is megbizonyosodtunk arról, hogy a strukturált adatgyűjtés és adatértékelés szükséges és ígéretes technika lehet az orvosi diagnózisok, terápia és kutatási folyamatok fejlesztésében, bemutatjuk saját strukturált kiértékelési sablonunkat.
Bár a kutatások főleg a papír alapú és az elektronikus adat közötti különbségre koncentrálnak, a szakirodalomban azonban már újabb tanulmányok eredményei meggyőző bizonyítékot mutatnak arra vonatkozóan, hogy a strukturált és szabványosított adatrögzítés javítja az egészségügyi dokumentáció minőségét. Az általunk kezelt nagy mennyiségű betegdokumentáció ésszerű tárolására egy saját adatbázist építettünk.
Az elektronikus információs rendszerek használata elősegíti az egészségügyi szakemberek dokumentációs tevékenységét. Magának az elektronikus adatnak a minősége különösen fontos a betegellátásban, de az elektronikus egészségügyi dokumentáció (EHR) nélkülözhetetlen információkat szolgáltatnak a minőségbiztosítás szempontjából is.
A strukturált és szabványosított dokumentációs módszer pozitívan befolyásolja a lelet minőségét, valamint lehetőséget teremt az adatok újra felhasználására, de bevezetése a kezdeti időszakban megnövekedett adminisztratív terheket róhat az egészségügyi dolgozók számára.
Roles of combined femoral and acetabular anteversion in pathological changes of hip dysplasia and hip reconstructive surgery
Authors: Liu Can , Xu Zheng , Zeng Jian-Fa , Song Zhen-Qi , Xie Yu-Yin , Tang Zhong-Wen , Wen Jie , Xiao Sheng
Published: May 2024

Combined femoral and acetabular anteversion is the sum of femoral and acetabular anteversion, representing their morphological relationship in the axial plane. Along with the increasing understanding of hip dysplasia in recent years, numerous scholars have confirmed the role of combined femoral and acetabular anteversion in the pathological changes of hip dysplasia. At present, the reconstructive surgery for hip dysplasia includes total hip replacement and redirectional hip preservation surgery. As an important surgery index, combined femoral and acetabular anteversion have a crucial role in these surgeries. Herein, we discuss the role of combined femoral and acetabular anteversion in pathological changes of hip dysplasia, total hip replacement, and redirectional hip preservation surgery.
Efficacy of stromal vascular fraction for knee osteoarthritis: A prospective, single-centre, non-randomized study with 2 years follow-up
Authors: Jeyaraman Madhan , Jeyaraman Naveen , Jayakumar Tarun , Ramasubramanian Swaminathan , Ranjan Rajni , Jha Saurabh Kumar , Gupta Ashim
Published: May 2024

BACKGROUND

Current osteoarthritis (OA) treatments focus on symptom relief without addressing the underlying disease process. In regenerative medicine, current treatments have limitations. In regenerative medicine, more research is needed for intra-articular stromal vascular fraction (SVF) injections in OA, including dosage optimization, long-term efficacy, safety, comparisons with other treatments, and mechanism exploration.

AIM

To compare the efficacy of intra-articular SVF with corticosteroid (ICS) injections in patients with primary knee OA.

METHODS

The study included 50 patients with Kellgren-Lawrence grades II and III OA. Patients were randomly assigned (1:1) to receive either a single intra-articular SVF injection (group A) or a single intra-articular ICS (triamcinolone) (group B) injection. Patients were followed up at 1, 3, 6, 12, and 24 months. Visual analog score (VAS) and International Knee Documentation Committee (IKDC) scores were administered before the procedure and at all follow-ups. The safety of SVF in terms of adverse and severe adverse events was recorded. Statistical analysis was performed with SPSS Version 26.0, IBM Corp, Chicago, IL, United States.

RESULTS

Both groups had similar demographics and baseline clinical characteristics. Follow-up showed minor patient loss, resulting in 23 and 24 in groups A and B respectively. Group A experienced a notable reduction in pain, with VAS scores decreasing from 7.7 to 2.4 over 24 months, compared to a minor reduction from 7.8 to 6.2 in Group B. This difference in pain reduction in group A was statistically significant from the third month onwards. Additionally, Group A showed significant improvements in knee functionality, with IKDC scores rising from 33.4 to 83.10, whereas Group B saw a modest increase from 36.7 to 45.16. The improvement in Group A was statistically significant from 6 months and maintained through 24 months.

CONCLUSION

Our study demonstrated that intra-articular administration of SVF can lead to reduced pain and improved knee function in patients with primary knee OA. More adequately powered, multi-center, double-blinded, randomised clinical trials with longer follow-ups are needed to further establish safety and justify its clinical use.
A model of dynamic planning of medical support for combat troops. A new look at the requirements and capabilities of the medical component
Authors: Gielerak Grzegorz Gerard , Murawski Piotr
Published: May 2024

Wprowadzenie i cel

Doświadczenia wojny w Ukrainie pokazują, że sukces w dziedzinie zabezpieczenia medycznego ludności może zapewnić jedynie służba kompletna, dopasowana do charakteru działań operacyjnych, korzystająca z rozwiązań pozwalających wykorzystać najnowsze osiągnięcia organizacyjne i technologiczne z obszaru zdrowia oraz opieki. Celem badania było opracowanie nowej metody dynamicznego planowania zabezpieczenia medycznego wojsk walczących poprzez modelowanie procesów opieki medycznej pola walki, służącej zwiększeniu skuteczności i efektywności zarządzania zasobami systemu ochrony zdrowia oraz poprawie zdolności operacyjnych wojsk walczących.

Materiał i metody

Modelowanie procesów opieki medycznej pola walki oparto na powszechnie uznanych czynnikach operacyjnych – sile, czasie i obszarze, rozszerzając tę grupę o dodatkowy, istotny z punktu widzenia organizacji pracy medycznych jednostek polowych parametr – bezpieczeństwo, przypisując jednocześnie wszystkim zmiennym właściwą, odpowiadającą przedmiotowi zagadnienia charakterystykę i interpretację.

Wyniki

Opracowano propozycję modelu kalkulacyjnego, na bazie którego skompilowano narzędzie analityczne pozwalające elastycznie dostosowywać oraz łączyć cele i potrzeby opieki medycznej – regulowane skalą i strukturą strat sanitarnych – z postępami w przebiegu operacji wojskowej w części zależnej od jej dynamiki oraz zdolności do prowadzenia manewru.

Wnioski

Proponowany model szacowania potrzeb medycznych w części dotyczącej zabezpieczenia operacji wojskowych jest zaawansowanym metodycznie i równocześnie łatwym w użyciu narzędziem wspomagania decyzji w zakresie planowania oraz organizacji opieki. Integruje wiedzę na temat występowania oraz rozpowszechnienia najważniejszych czynników określających warunki i możliwości prowadzenia pomocy medycznej oraz potrzeby i oczekiwania wynikające z zamierzeń taktycznych i operacyjnych. Optymalizuje procesy zabezpieczenia medycznego pola walki. Ogranicza ryzyko błędów w najbardziej wrażliwych, kluczowych dla powodzenia operacji wojskowej obszarach. Wzmacnia odporność systemu ochrony zdrowia na działania hybrydowe i militarne, dostarczając kluczowych informacji dotyczących bieżących potrzeb w zakresie jego organizacji i funkcjonowania w powiązaniu z planami taktycznymi, operacyjnymi oraz strategią obrony państwa. Prowadzona za jego pomocą koncentracja i koordynacja zasobów medycznych, zarówno natywnych, przypisanych do ugrupowania bojowego, jak i znajdujących się w przestrzeni operacyjnej, tworzy środowisko zapewniające wysoką skuteczność i efektywność udzielanej pomocy.
Kala Pathar (Paraphenylenediamine): the Frequent and fatal poisoning
Authors: Imran Sadia , Shah Syed Zulfiquar Ali , Bibi Ishrat , Qadeer Farheen , Khan Deeba , . Azmira
Published: May 2024

Pakistan doesn't keep exact records of deaths or suicides because it doesn't have any vital records. The world's average suicide death rate for both men and women in 2017 was 9.98 per 100,000 people. In Pakistan, the projected age-adjusted suicide rate is 4.4 per 100,000 people. Three countries that are close by have suicide death rates of 13.33, 5.73, and 7.55 per 100,000 people, respectively. Recent statistics show that self-harm is becoming a major public health issue in Pakistan, even though the estimated rate is still low1. About 96% of the people who live in Pakistan are Muslims. Like most major faiths, Islam says that suicide is a sin that can't be forgiven. This could be a big reason why people don't commit suicide, as shown by the fact that rates are usually much lower in Muslim countries than in non-Muslim countries. Because of religious beliefs,
Effect of Nutritional Status in Postoperative Recovery among Surgical patients
Authors: Ali Zulfiqar , Rehman Shafique-Ur- , Jameel Muhammad Aamir , Majid Haroon Javaid
Published: May 2024

Aim: To draw a comparison between the frequencies of postoperative complications between malnourished and well-nourished patients and to determine the impact of pre-operative nutritional-status on the postoperative recovery among surgical patients. Place and duration of study: This was a cross sectional comparative observational study by design which was conducted in the Department of Surgery, Shaikh Zayed Hospital Lahore Pakistan form June 2014 to December 2014. Study Design: Cross sectional comparative study. Methodology: Four hundred volunteer individuals were taken in the study. Written, informed consent was taken from all the included individuals. All the included individuals were weighed by a digital scale and their heights were measured using the height scale, and thus their Body Mass Index was calculated according to the following formula, before the surgery; BMI less than 18 or more than 25 and was considered as Malnutrition. Also Hemoglobin, TLC (Total Lymphocyte count = % Lymphocytes X WBC/ 100),serum albumin was measured and if found impaired, patient was considered to have under-nutrition. Now after surgery the patients were followed for 5 days postoperatively and any complication was noted. Occurrence of any single complication was treated as presence of complication. Total number of days stayed at hospital postoperatively were also calculated. Data was analyzed using SPSS 20. Results: There was significant difference with respect to major complications and side effects between well-noursihed and malnourished cases. More number of cases developed infection in the malnourished groups as compared to other group. Conclusion: Patients must be kept under observation for their nutritional status postoperatively for a specific duration so that morbidities could be reduces and patients can get back to work earlier. Keywords: Malnourish, Surgical Patients, Nutritional Assessment, BMI
Clinical Risk Factors Associated with Miscarriage
Authors: Shaikh Aneela Gul , Lakho Nusrat , Shah Sabahat Fatima
Published: May 2024

Aim: To identify the risk factors in patient came in OPD and in emergency with sign and symptoms of miscarriage. Method: Retrospective Cross Sectional was conducted at the Department of Obstetrics & Gynaecology, Lady Willingdon Hospital Khairpur Medical College Khairpur Mir’s from 1st January 2021 to 31st December 2022. Two thousand, one hundred and thirty patients of miscarriage were enrolled. Patient with congenital abnormal foetus and still birth were not included. Results: The majority of patients were more than 35 years of age was 974 (41%). It was also noted that abortion was more common in multigravida 1215 (57%). The risk factors of abortion were 1735 (81.4%) had lack of history of taking folic acid and multivitamins. Practical Implication: Poor socioeconomic status, lack of knowledge, illiteracy, marital problems, and physical abuse are significant risk factors for miscarriage, necessitating the provision of appropriate clinical and supportive information. Conclusion: The risk factors of miscarriage include age of mother, lack of history of taking folic acid and multivitamins during antenatal period increased body mass index and previous history of miscarriage physical abuses, history of infertility and h/o of smoking Berri and Hukka are significant. Keywords: Risk factors, Miscarriage, Outpatient Department, Incidence
Role of Ultrasound in the Diagnosis of Non-Alcoholic Fatty Liver Disease (NAFLD)
Authors: Salam Abdul , Malik Ayesha , Farid Nadir , Lali Mehwish , Farid Muhammad Imran , Wadood Abdul , Gawhar Sani , Muhammad Sobia Wali
Published: May 2024

Background: The most prevalent liver illness, nonalcoholic fatty liver disease (NAFLD), is characterized by abnormal fat buildup in the hepatocytes without a substantial alcohol consumption history or secondary causes of fatty liver disease. Aim: This study aims to assess ultrasound's diagnostic utility in NAFLD. Material and Method: In the Hayatabad Medical Complex (HMC) in Peshawar, Pakistan, a cross sectional study with convenient sampling technique was conducted over six-month. This study received permission from the Institutional Research and Ethical Review Board (IREB) of HMC Hospital, and Open-Epi determined the sample size of 250 patients with a 95% confidence interval and a 5% margin of error. A certified sinologist conducted the abdominal ultrasound. The right arm was extended to its maximum abduction while the participants were positioned in the dorsal decubitus position. Using a right intercostal technique, the right liver lobe was seen, and a representative parenchymal region was identified without compromising the main vascular. The data were gathered through Questionnaire and analyzed using SPSS version 26. Results: There were 250 participants, with 55.4% men and 44.2% women. Patients between 40 and 49 accounted for 38.4% of the affected population. The most common conditions among patients with NAFLD were mild severity (49%) and abdominal discomfort (47.4%). Only (8%) of participants had liver cirrhosis before NAFLD while (91.6%) of patients lacked liver cirrhosis before NAFLD. When treating suspected NAFLD, 83.3 percent of patients preferred the Ultrasound modality initially, and more patients received a primary ultrasound diagnosis. Practical Implication: Ultrasound is the most commonly used modality because of their availability and low cost but its role in NAFLD is not fully diagnosed and evaluated. This study aims to evaluate the proper use of the Ultrasound modality in NAFLD for the benefits of patients to be diagnosed initially with Ultrasound so that it may not lead to a serious problem. Conclusion: A valuable non-invasive imaging technique for the diagnosis of non-alcoholic fatty liver disease (NAFLD) is ultrasound. Most patients first favor ultrasound, which is considered the leading imaging modality for NAFLD suspicion. The majority of NAFLD patients were middle-aged and male. Keywords: Abdominal pain, Fatigue, Liver cirrhosis, Non- Alcoholic Fatty Liver Disease, Ultrasound
Prevalence of Sexual Dysfunction in Patient with Subclinical Hypothyroidism and Subclinical Hyperthyroidism
Authors: . Sana , Khan Zakirullah , Babar Bakht , Khan Jamal Ahmad , Khan Azmat Ali
Published: May 2024

Introduction: Thyroid disease as well as sexual dysfunction is both prevalent disorders that can significantly impact one's quality of life. Objectives: To determine the prevalence of sexual dysfunction in patient with hypothyroidism and hyperthyroidism. Study design: Cross sectional study Settings: Department of Diabetes, Endocrinology and Metabolic Diseases, MTI Hayatabad Medical Complex, Peshawar from December 2022 to May 2023. Materials & Methods: The study included adult individuals (aged 18 and above) with a confirmed diagnosis of hypothyroidism. Individuals with pre-existing sexual dysfunction unrelated to hypothyroidism, those with comorbidities affecting sexual function (diabetes, cardiovascular diseases), and pregnant or lactating women were excluded. Additionally, individuals unable to complete the required questionnaires or participate in the study procedures were not considered for inclusion. Participants provided demographic details, including age, gender, and relevant medical history. Thyroid function was assessed through serum levels of thyroid-stimulating hormone (TSH), triiodothyronine (T3), and thyroxine (T4). Statistical analysis was performed using SPSS version 22.