bluuebunny/crossref_metadata_2025 huggingface dataset:
Examining the Varied Culinary Practices and Nutritional Patterns: A Comprehensive Analysis of Eating Habits Amongst Student Populations in Educational Settings
Authors: Arun Dr. R. , Srivastava Dr. Saurabh , Sireesha Rajeyyagari , Dr. A. Thilagara
Published: September 2024

Comprehensive bibliometric analysis represents an in-depth exploration of the dynamic and evolving landscape of research concerning eating habits among students, leveraging insights extracted from a vast dataset comprising 563 Scopus-indexed publications spanning diverse academic disciplines. Contrary to anticipated trends, the study's findings reveal a surprising absence of discernible patterns in the convergence of eating habits within the examined literature. This unexpected revelation challenges existing assumptions and underscores the fluidity and complexity of scholarly inquiries into the dietary behaviors of students. Notably, Spain emerges as a crucial contributor, assuming a leadership role in the distribution of documents related to eating habits, thereby highlighting its substantial influence in shaping the global discourse on this pertinent subject. Moving beyond a conventional panoramic overview, this study delves into the intricate fabric of relationships and collaborations within the domain of eating habits research among students. Unraveling these complex dynamics provides nuanced insights into the significant authors, organizations, and seminal papers that have played instrumental roles in advancing the knowledge base within this realm. The dual-focus approach not only enriches our understanding of the multifaceted research terrain but also highlights key contributors and influential organizations that have made noteworthy strides in shaping the discourse on eating habits among students. Furthermore, the analysis identifies essential keywords such as "body mass," "obesity," and "stress" with a notably high frequency of occurrence. These keywords serve as thematic markers, indicating the central dimensions of the scholarly conversation surrounding student dietary behaviors. This revelation underscores the critical relevance of these themes in the existing literature and points towards avenues for further exploration and investigation. By adopting a bibliometric approach, this study not only provides a comprehensive snapshot of the current state of research on eating habits among students but also offers a roadmap for future exploration, emphasizing key contributors, themes, and the intricate collaborative networks that define this evolving field. Researchers, practitioners, and policymakers alike stood to benefit from the nuanced insights gleaned from this expansive analysis, contributing to a more holistic understanding of the multifaceted aspects of student nutrition.
Mapping the Landscape: A Bibliometric Analysis of Online Learning in Higher Education
Authors: Mishra Dr.Biswo Ranjan , Dr. Keerthan Raj  , Dr.A.Shameem  , Dr M R Vanithamani  , Kiran Kumar Thoti  , Turlapati Venkata Ramaiah
Published: September 2024

E-learning is now a requirement in all educational institutions, including schools, colleges, and universities, because of the COVID-19 pandemic crisis. The use of online learning methods requires teachers and students to adapt to maintain business as usual despite several challenges. Additionally, it alters how students behave. Some of them struggle with anxiety and sadness. This essay investigates how behavior of students is affected by online learning. Teaching staff, including parents, recommend that the government sector take initiatives to assist students who have limited access to the internet and devices—which are the primary requirements to be able to participate in online classes—while also boosting student engagement in virtual learning, particularly during this crucial pandemic.
Minimally Invasive Plate Osteosynthesis for Comminuted Fractures of Long bones: A Prospective Study on Outcomes and Complications
Authors: Prabhakaran A.K. , Subash Yeshwanth
Published: September 2024

The surge in comminuted bone fractures, attributed to modern lifestyles and increased trauma incidents, poses significant challenges in management. Traditional open reduction and plating methods, while effective, are associated with drawbacks like delayed union and higher infection rates. The evolution of MIPO (Minimally Invasive Plate Osteosynthesis) seeks to overcome these limitations. The potential effects of MIPO in the management of severely comminuted long bone fractures are investigated in this work.
The Saveetha Medical College's Department of Orthopaedics carried out a prospective study from March 2022 to March 2024. Patients aged 20 to 60 with fractures of the femur, tibia, and humerus resulting from road traffic accidents were included. The AO Fracture classification system was utilized, and MIPO techniques were employed for fixation. Clinical and radiological assessments were conducted at various follow-up intervals. Statistical analysis using IBM SPSS Version 22.0 assessed outcomes, with a P-value<0.05 countedas significant.
MIPO was performed on twenty-four male patients, ages averaging 34.4 years, for severely comminuted fractures. The distal 1/3 of the femur, the tibia, and the humerus shaft were among the fractures. Union was rapid in 15 cases, with delayed consolidation in two requiring secondary bone grafting. Functional outcomes assessed using the Neer–Grantham–Shelton Criteria, demonstrated excellent outcomes- 65%, good- 30%, and fair- 5% of events. Complications included infection (5%), wound gaping (5%), joint stiffness (25%), and limb length discrepancy (20%).
This study reinforces MIPO as a promising approach for severely comminuted fractures, showcasing excellent union rates and functional outcomes. Studies highlight its advantages in preserving soft tissue and periosteal circulation. The shift from anatomic reduction to optimal stability in such fractures aligns with current trends. Complications, though present, are manageable. The study contributes to the growing body of evidence supporting MIPO, emphasizing its potential advantages in minimizing surgical trauma and maintaining biological stability. Further research, including comparative studies and exploration of other fixation methods, is warranted for a comprehensive understanding of MIPO's role in fracture management.
To Assess the Functional outcome of Inflammatory arthritis of Knee following a Total Knee Replacement in a Tertiary Care Centre
Authors: Krishnan Arjun , Subash Yeshwanth
Published: September 2024

Introduction : Inflammatory arthritis, particularly RA, can lead to significant joint destruction and functional impairment, necessitating interventions such as TKA. Despite medical therapy, severe joint damage may occur, warranting surgical intervention. This study assesses the functional outcomes post-TKA in patients having inflammatory arthritis. Materials and Methods: Patients who received TKA for inflammatory arthritis were included in this prospective observational cohort research, specifically RA, between 2019 and 2023 at Saveetha Medical College, Chennai. Clinical, radiological, and functional results have been assessed using the American Knee Society scoring system. IBM SPSS version 22.0 was utilized for analysis of data, p < 0.05 is the threshold for statistical significance. Results:Twenty TKAs have been performed for RA, with all patients successfully followed up. The mean age of the patients was 58.5 years, and the majority were female. Before TKA, the average length of RA was 7.24 years, and all patients were in stage IV illness. Preoperative and postoperative knee society scores showed significant improvement, with average scores of 58.15 and 96.15, respectively. Functional scores also demonstrated substantial enhancement post-TKA, with an average increase of 130%. Radiological assessment revealed no evidence of lysis in any patient. Conclusion: Significant inverse relationship among the postoperative functional score and the length of the disease and the involvement of other joints. Utilizing the American Knee Society and functional scoring systems allows for objective prediction of surgical success. This can motivate surgeons and treating physicians to enhance care for RA patients.
Assessing Initial Functional Outcomes Following Arthroscopic Release for Stiff Shoulder in Periarthritis Shoulder
Authors: Sekar Nitheesh , Subash Yeshwanth
Published: September 2024

Adhesive capsulitis can manifest as either primary/idiopathic or secondary, often linked to systemic illnesses. Primary adhesive capsulitis is characterized by limited range of motion without underlying systemic or precipitating shoulder conditions and lacks intrinsic pathology. In contrast, secondary frozen shoulder is associated with identifiable intrinsic factors such as diabetes, thyroid disorders, cardiac disease, stroke, prolonged immobilization, trauma, and rotator cuff disease. Our study aims to assess the initial functional outcomes, average recovery duration, and related comorbidities in arthroscopic release for adhesive capsulitis of the shoulder.The study was carried out at the Department of Orthopedics in Saveetha Medical College and Hospital, Thandalam, spanning from June 1, 2022, to June 31, 2023. It comprised 30 patients diagnosed with adhesive capsulitis who met specific criteria. The treatment regimen consisted of Arthroscopic Release followed by intensive physiotherapy and prescribed home exercises. Follow-up appointments were scheduled at regular intervals to track progress, using assessment tools like the UCLA Score and VAS score, and all data were meticulously recorded in a standardized proforma.30 individuals who met specific criteria were diagnosed with adhesive capsulitis. Of these, 12 out of 18 participants were female, and 16 patients experienced more frequent impairments on the left side. The average age of the patients was 65 years, ranging from 57 to 78 years old. Stage 2 was the most common among the approximately 19 patients. Prior to surgery, the UCLA score had a mean of 23, ranging from 18 to 26, while the mean preoperative VAS score was 8, with a range of 7 to 9. Following surgery, significant improvements were observed in the UCLA score, ranging from 26 to 35, and the post-operative VAS score ranged between 2 and 5. In our study, arthroscopic release appears as a safe procedure with favourable postoperative results. This consequently enables early mobilization of the shoulder joint and decreases complication rates.
How do Patients Receiving Antiretroviral Therapy (ART) at A Dedicated ART Center in Bhagalpur Demonstrate Observable Patterns and Outcomes in an Observational Study?
Authors: Choudhary Raj Kamal , Singh Amrendra Kumar , Ojha Shubham , Verma Vinay Kumar , Kumar Avinash , Bhagat Ravi Kishan , Gupta N K , Kumar Abhilesh , Pervez Anjum , Fatima Sidratil
Published: September 2024

Ours study provides a comprehensive overview of the HIV/AIDS landscape in Bhagalpur, Bihar, focusing on patients receiving Antiretroviral Therapy (ART). Conducted over six years, involving 10,355 participants, the research explores demographic details, treatment outcomes, and treatment-seeking behaviors. Notably, 100% participation reflects the community's engagement, with detailed analyses of gender-specific registrations, treatment initiation, and outcomes. The study delves into patients' geographic origins, travel distances, and factors influencing their preferences. Insightful discussions on perceptions regarding HIV and ART underscore societal challenges. Positive aspects include family support and awareness, yet concerns like substance use and travel barriers need attention. The study concludes with recommendations for targeted interventions to enhance HIV/AIDS care effectiveness. Limitations highlight the need for broader community comparisons, emphasizing the study's contribution to shaping future research and healthcare strategies. The acknowledgment expresses gratitude for mentorship and collaborative efforts in completing the project.
Individual Psychological Profiles And Their Influence On Self-Regulatory Behaviour In Sport
Authors: Gakh Roman , Panok Vitalii , Furman Oksana , Lunchenko Nadiia , Korniienko Serhii
Published: September 2024

The purpose of this paper is to study how individual psychological characteristics of an athlete affect his/her ability to effectively self-regulate during training.
In the course of the study, the testing method was applied (Cognitive Strategies in Sport Scale and Psychological Stress Measurement). Methods of descriptive statistics for the analysis of the mean value and square deviation and Pearson's correlation coefficient (chi-square).
The results of the study showed that there is a statistically significant difference between the mean values of all cognitive strategies. The most pronounced differences were observed between emotional control and other strategies, as well as between focusing attention and other strategies. This suggests that emotional control and attention focus are key cognitive strategies for achieving success in sport. In addition, psychological aspects and individual personality traits of athletes significantly affect their ability to self-regulate during training, which confirms the importance of taking these factors into account when developing training programmes.
The study confirmed that emotional control and focus are key cognitive strategies for achieving success in sport. Individual psychological characteristics of athletes have a significant impact on their ability to effectively self-regulate during training. This highlights the importance of integrating psychological training into training programmes to improve athletes' performance. Further research should focus on developing methods to help improve these aspects.
Spatial Analysis of the Effect of Aspergillus spp Fungus on the Soil of the Plateau (Najaf - Karbala)
Authors: Al-Salami Maryam A. Rahim , Menkhi Saadia Akol
Published: September 2024

This study investigated the spatial and temporal variation of Aspergillus spp fungus in the soil of the Najaf-Karbala plateau, covering Najaf district center and Al-Haidariya district. Soil samples were collected from 36 sites over four seasons and analyzed microbiologically to identify types and quantities of Aspergillus spp fungus. Spatial analysis techniques, including GIS and spatial autocorrelation, were used to examine the distribution of Aspergillus spp fungus across the study area. The results showed significant spatial and temporal variation in the occurrence of Aspergillus spp fungus, with highest concentrations found in autumn and spring seasons. The study highlights the environmental hazard posed by Aspergillus spp fungus in the Najaf-Karbala plateau soil, with potential health risks for humans, animals, and plants. Further research is needed to understand the sources and drivers of Aspergillus spp fungus presence and to develop strategies for mitigating its environmental and health impacts.
The Legal and Public Health Implications Of Digital Health Technologies
Authors: Chandrakar Ekta , Dahiya Aman
Published: September 2024

To reduce the negative effects of digitization, normative advice in international human rights legislation incorporates digital health into ethical and human rights frameworks. The use of digital health technology for universal health coverage (UHC) is acknowledged to have benefits, but its implementation must be based on respect for human rights, equity, and ethics, as well as upholding norms of acceptable quality, safety, and morality. The WHA acknowledged the necessity to use digital health technologies in the wake of the COVID-19 pandemic in 2020, but stressed that in doing so, they must "pay particular attention to digital inclusion, patient empowerment, data privacy and security, legal and ethical issues, and the protection of personal data." This paper's goal is to critically assess the proposed legislative framework and policy that regulate digital health technologies in India, as well as the implementation of digital health.
Environment Aspects and Daily Life-Threatening Risk Prediction for Improving Public Health Using Ensemble Learning Techniques
Authors: Dewangan Omprakash , Prakash Vasani Vaibhav
Published: September 2024

Increasing work nature in the fastest world need relaxing to maintain public health is important. But the continuous imbalance of work nature in human daily life doesn’t have time to consecrate the health with leads life threatening facts such as work tension, management stress, job professional, family needs, improper periodic work cycle, and soon. By analyzing the daily public life threatening risk prediction based on Feature selection and classification to category the public health to recommend for phycological treatment.  By suggesting treatment schedule are important to balance the public health Lifecyle to make stress free life to spent with nature.  Most of prevailing techniques analyse the life-threatening issues, but the features are improperly to taken without the mutual relation cause poor accuracy in precision and classifications rate with more false prediction rate. To tackle this issue, to propose an optimized ensemble learning Techniques based on multi scalar support vector machine (MSSVM) with deep scaled XGboost classifier (DSXG-boost) to improve the prediction accuracy. Initially the public life Cycle dataset is collected and to make normalization using Min-max normalization. Then the Public Life Threat Impact Rate (PLTIR) is analysed to marginalize the heath affecting features. Then then stress margin dependencies feature limits are selected with support of MSSVM. The selected features are grouped in cluster margins and classified with deep scaled XG boost algorithm to predict the active and inactive heath margin be categorized by risk threaten class. The proposed system prove the prediction accuracy in higher precision are by selecting mutual dependencies of health affection feature limits and best recall rate to improve the performance. Based on the predicted class, the categorized life threaten risk peoples are recommends to make phycological treatment to protect the public life cycle.
Health Promotion and Disease Prevention Through Pharmacy Interventions
Authors: Dewangan Tripti , Dhimar Chandra Pratap
Published: September 2024

The rapidly developing discipline of health informatics offers enormous potential to enhance the prompt administration and high-quality services provided by the healthcare system. One invention that has significantly altered the world is information technology. Health informatics is the application of practical information technology features to healthcare practices with the goal of improving patient outcomes. It significantly facilitates information sharing amongst medical experts. In clinical practice, having reliable, evidence-based data readily available is really beneficial. There are several facets to health informatics. The first is the keeping of medical records. This includes computerised prescribing and electronic management of medical records. It is beneficial to have quick access to all of a patient's medical records. Health experts' time can be greatly saved by this. The availability of a sizable patient population's health data, which may be used for population-based investigations and research, is another benefit. A component of health informatics, clinical decision support systems (also known as CDSS) assist medical professionals, particularly physicians, in making decisions regarding patients throughout their regular practice. They are created as applications or software to be utilised in patient care.
Resilience and Adaptation: Investment Metrics of Indonesian Healthcare Companies Before and During the COVID-19 Pandemic
Authors: Irhamni Firly
Published: September 2024

The impact of dividend policy and stock valuation (price earning proportion and price to book value) on the prices of healthcare industry stocks listed on the Indonesia Stock Trade somewhere in the range of 2016 and 2021 is examined in this study. The research data used in this quantitative analysis are secondary data. This study included eighteen healthcare sector companies in its sample. Purposive sampling is the methodology used in this study, and SPSS 24 is the analysis tool. We explained the relationship between stock prices, dividend policy, and stock valuation. We order the variables into pre-pandemic and during-pandemic categories subsequent to testing them for like clockwork. That's what the experimental results demonstrate, for all periods, the earning-per-share notation has a significant impact on stock prices. Stock valuation, on the other hand, has a significant impact on stock prices, as does the final dividend policy with dividend payout proportion and dividend per share. Meanwhile, results from the pre-pandemic time frame indicate that EPS and DPR didn't significantly influence results; results from the pandemic time frame indicate that stock valuation didn't significantly influence stock price. This research provides fresh insights into what the recovery of economic exposure means for corporate conduct in Indonesia, where persistent financial and economic pressures from stock market unpredictability give substantial sources of uncertainty.
The Impact of Health Laws and Policies on Marginalized Communities
Authors: Shrivastava Saloni Tyagi , Singh Abhay Pratap
Published: September 2024

International law has consistently upheld the importance of human health as a fundamental necessity. Public international law gives rise to the topic of international health law. Many human rights articles, accords, regional instruments, etc., declare this right to the best possible standard of health. The focus of international health law is on an individual's ability to function satisfactorily. It also suggests that in addition to ensuring access to healthcare services, attention should be paid to creating healthy environments, which includes safe drinking water, sanitary conditions, health-related details, education, safe and healthy work environments, and healthy living spaces. Due to its emphasis on the global protection of individual human health, the right to health is a fundamental human rights criterion in the field of international health law. This book emphasises the significance of health legislation and policies and the necessity of attempting to achieve health fairness.
Study on Improving Healthcare Operational Performance through Talent Management Strategies: A Public Health Initiative
Authors: Sehgal Dr. Rajesh , Sharma Dr. Ravinder
Published: September 2024

The importance of talent management in enhancing the operational efficacy of public health system is becoming increasingly apparent to the general public. This study seeks several approaches to improve the public health wellness talent management procedures. Staffing strategies, methods for attracting and retaining employees, career development foundations and management growth are all important factors to take into account. By using this measure, hospitals can enhance overall operational efficacy and patient care results by managing issues such as staff shortages, uneven skills and worker stress. Constructed hypothesis are aimed at examining the linkages between Talent Engagement (TE), Talent Growth (TG), Talent Longevity (TL), Skill development (SD), and Talent management (TM) in the public health settings. ANOVA and F-test are utilized for the survey data, which encompasses the 350 employees from the hospital. To measure the employee satisfaction, remote data collection methods were also employed. Enhancing public care standards, workforce effectiveness, and long-term public health performance are the three primary objectives of the findings
A Unification of Fog-Cloud Computing for Data Agitation and Guard Intensification in Industrial Health Care Security
Authors: Biswas Debarghya , Tiwari Ankita
Published: September 2024

The development of Fog computing is a decentralized environment in which the data processing, storage and applications are processed between the located server in a cloud environment. By increasing the Internet of things (IoT) and remote storage, the communication in cloud become more sophisticated by processing the data safely and securely.  Healthcare data is important which contains medical information and processed centrality in the public environment through IoT, due to increasing security breaches they need to protect depends on the security applicants. All over the centralized data computing are accessed by virtual environment through remote protocol doesn’t provide safety in healthcare industry. To resolve this problem, to propose as Unification of fog-cloud computing for data agitation and guard intensification (DA-GI) in Industrial Health Care Security.  The Medical Data Health-Care (MDHC) records are stored in Cloud datacenters and the Fog layer based on the guard intensity and the key is provoked for ingress the file. The activity logs are controlled and monitoring from cloud serves sustains the Activity Log, Risk Table and Health Records. To introduce a cryptographic approach based on advanced encryption standards (AES) to protect data and authenticity verification server. The key verification process based on security gateway, Fog cloud server depends on user access rights provided to the user. During the key validation, role of permission to the user s verified and agitate to allow access rights to the verified service access. The proposed system produce high security compared to the other system as well in all security concerns of role, authentication and verification to process data safely.
Analysis of Pharmaceutical Sciences and Public Health Applications
Authors: Vaishnav Venu Anand Das , Agrawal Mr. Ashish
Published: September 2024

Growing in frequency in both rural and urban parts of India, growing percentage of people at risk of diabetes, Indian population's genetic susceptibility to diabetes risk factors related to the environment, Globalisation causing a decline in physical exercise Some of the challenges that the disease poses in India are low patient awareness of hypertension, undiagnosed hypertension due to a variety of factors such as low healthcare facilities and economic status, inadequate disease control, and an increasing incidence of complications related to hypertension. Although there are solutions, the healthcare team will need to work in tandem with the clinician who is battling the illness on an individual basis. This will prevent the patient from receiving the proper care, the clinician from being able to listen to the patient's problems and find solutions, the patient from receiving the psychological support they need for a chronic illness, and the nation from suffering from economic hardship after the patient's illness. The purpose of this study was to identify the services provided by pharmaceutical care and evaluate the barriers to pharmaceutical care in various settings in order to provide relevant recommendations.
Cybersecurity and Compliance in Healthcare: A Study on Key Management and Other Regulatory Requirements
Authors: Vij Priya , Prashant Patil Manisha
Published: September 2024

Typically, WSNs are implemented in several applications with various topologies. Nodes use wireless mode of communication, and unattended areas are typically selected for WSN deployment. Attack risk is higher in WSNs. Furthermore, the WSN nodes have severe resource constraints. It is quite difficult to provide security in such a setting. Numerous protocols for key management chores and encryption strategies for maintaining security in the WSN environment have been documented in literature. The criticality of the data being transferred over the network determines how complex the assault will be. Applications that monitor agriculture, for example, are safe from attacks. However, applications related to the military and healthcare could attract attackers who are far more skilled. Applications that involve process control and habitat monitoring attract attackers with medium to low skill levels. There isn't a single protocol available right now that could be flexible enough to meet the different requirements of the apps, which typically have variable security requirements. For these different applications, there are differences in the key management task, which is strongly related to the security requirements. As a result, the precise kind and complexity of the key management technique must be chosen and built in accordance with the necessary level of security, the capabilities of the hardware devices available, and the network topology that is used.
Application of Nano Technology in Disease Prevention Through Pharmacy Interventions
Authors: Sahu Birendra Kumar , Aman
Published: September 2024

India spent more than 50 years working to combat tuberculosis. When the National Tuberculosis Programme of India (NTP) was first launched in 1962, it was intended to treat patients at home with self-administered conventional medication regimens. The key to a successful formulation is getting the active ingredient to the desired location with the least amount of discomfort and adverse effects. Controlled release technologies and drug delivery systems are helpful in a variety of therapeutic procedures. For instance, the focused therapy approach effectively delivers the medication while lowering treatment costs. To make a drug delivery system successful and sensible, factors including a preset release pattern, drug stability in the system and in the environment in which it is released, biodegradability, and penetration across a particular biological barrier for targeted administration are important to consider. This work developed a medication delivery model based on a cubic structure.
Knowledge and Awareness About Breastfeeding Among Postnatal Mothers in a Private Medical College
Authors: A Dr.Asha , Balakrishnan Dr. Rangesh kumar , Sahayam Dr.T.Priya Vadhana , KumuthaJ Dr.
Published: September 2024

Background: Breastfeeding is essential in any infant’s nutrition and growth. There are various misconceptions and cultural beliefs regarding breastfeeding which can hinder breastfeeding and its continuation by the mothers.
Objective: To describe the current level of knowledge and awareness about breastfeeding among postnatal mothers in private medical college.
Methods: A Clinic based cross-sectional review was completed in the post-pregnancy ward of Obstetric division of the Saveetha clinical school and medical clinic between June 2021 toAugust 2021. Information were gathered through interview utilizing a semi-organized poll. Datawere went into Microsoft succeed and engaging examination was finished.
Results: A very small percentage of postpartum mothers are aware of the significance of avoiding prelacteal feeding, early breastfeeding, exclusive breastfeeding, burping, and breastfeeding on demand. However, more than half of postpartum mothers are aware of the health benefits of breastfeeding, the benefits of colostrum, and the bonding benefits of breastfeeding. Additionally, they are informed about whether mothers with HIV or tuberculosis can breastfeed.
Big Data-Based Optimized Deep Learning Model for Improving Performance of Electronics Health Care Data
Authors: Bhaskar Rajeev Kumar , Kumaraswamy Balasubramaniam
Published: September 2024

Bigdata analytics is a new area of supervised analytics that healthcare analytics has moved into. Healthcare data is transmissive, incremental, and substantial, and it has pre-set thresholds for classifying patient conditions and diseases. The necessary understanding of disease occurrences is applied to the analysis of this data. The research project introduces healthcare data analytics with a novel framework that leverages unstructured data for the classification of healthy and unhealthy samples in order to understand the nature of healthy and unhealthy labelled classes. This is motivated by the fact that healthcare data is informative and voluminous in nature. Additionally, the unknown samples' health status is predicted using the supervised knowledge. Each model presented in this work is supported by accuracy and a computational complexity model.
Parental Stress and Coping Strategies in Parents of an Educational Institution in Times of COVID-19
Authors: Huamán Lisseth Beatriz Chanduvi , García-Flores Lizzeth A. , Ordoñez Sara Esther Liza , Larre Yen M. Bravo , Hernández Ronald M.
Published: September 2024

As a consequence of the COVID-2019 pandemic, parents had to adapt to a new way of life, facing different stressors through the use of coping strategies. The aim of the study was to establish the relationship between parental stress and coping strategies in parents of an educational institution in the district of Cartavio, Peru. The research was descriptive-correlational, non-experimental cross-sectional design, with a sample of 108 parents, using the Parental Stress questionnaire, in its reduced version and adapted to the Peruvian context, and the Stress Coping Estimation Inventory (COPE). The results indicate a positive relationship between parental stress and the strategy of behavioral disengagement; parental stress levels belonged mostly to the medium category with 67.5%; the predominant stress coping strategies were active coping and positive reinterpretation - personal development, both with 18.5%. It is concluded that there is a relationship between the parental stress strategy and behavioral disengagement.
Design of Nanocarriers for Chemotherapy of Prostate Cancer
Authors: Mire Sanjay Kumar , Sinha Jitendra Kumar
Published: September 2024

Any part of the body might become cancerous. It begins when regular cells are pushed out by out-of-control cells. This can spread to other parts of the body and interfere with normal bodily functions. Globally, cancer is considered to be a huge burden that will only get worse as the population ages and grows. Given the various drawbacks and adverse effects of the traditional formulations, novel strategies for medication delivery to prostate cancer cells are being researched and explored. With their many advantages over traditional chemotherapy, including improved drug solubility, protection from macrophage uptake, which lengthens the drug's blood residence time, and controlled drug delivery to the target prostate cancer, polymeric nanoparticles have been identified as promising candidates for drug delivery to prostate cancer.
Incident Response and Threat Intelligence in Healthcare: A Study on Cybersecurity Incident Management
Authors: Deshmukh Rajesh Keshavrao , Shrivastav Mohit
Published: September 2024

India and other Asian nations are seeing an unparalleled pace of advancement in the modernisation of their healthcare systems. In this endeavour, information technology is crucial. Though the healthcare industry has made great progress, information security is still lagging behind the protection requirements attained in technologically developed nations such as the United States and the United Kingdom. This study is an honest attempt to pinpoint vulnerabilities and dangers in the field of cybersecurity and offers a few targeted remedies in three main domains: risks, vulnerabilities, and IoMT. Using a qualitative research methodology, this research culminates in the creation of a security maturity model for Indian healthcare. Furthermore, in light of these attacks, the well-known National Institute of Standards and Technology (NIST) risk assessment system and its guiding principles are examined. Evaluating the risks intrinsic to these hacks analytically becomes crucial given the comparatively low information risk management maturity levels in Asian healthcare organisations. While several nations in Asia and throughout the world are battling the COVID-19 outbreak, cybercriminals have been attempting to spread misinformation about vaccines. Additionally, some people and organisations are attempting to undermine specific vaccines in order to promote their COVID-19 treatments. Hacking research data, virus testing, and clinical studies that reveal side effects or possible issues are of particular interest to profit-seeking businesses. The secure methodology for identifying network attacks is suggested by this study.
Respond to Public Health Emergencies and The Law Preparedness Challenges and Solutions
Authors: Sharma Paluck , Singh Samiksha
Published: September 2024

Laws are a very powerful tool for defending human rights. These could be parliamentary enactments, local panchayat regulations, international conventions, or constitutions. Every facet of the emergency and public health response is based on law and policy. Laws made it possible to establish lockdowns, declare states of emergency, and, more recently, speed the clearance process for vaccines. The removal of antiquated laws, regulations, and backup plans frequently revealed them to be insufficient or out-of-date, necessitating the quick creation of new legislation. Never before have so many laws concerning one incident been passed in so many nations in such a short period of time. Communities are kept safe and lives are saved by domestic legal preparedness for catastrophes, which includes public health emergencies. The cornerstones of disaster risk management are law and policy, which establish guidelines for the who, what, and when of emergency response operations. When preparedness and response efforts lack a solid legal foundation, they may be disorganised and ineffectual, which frequently causes the most vulnerable individuals to wait longer for critical assistance. This essay suggests that there is a general deficiency of robust public health emergency legislation as well as a lack of legal readiness for such situations.
Self-Management Effect on Preeclampsia in Pregnant Women at RSI Jemursari Surabaya
Authors: Afiyah R. Khairiyatul , Umamah Faridah , Rusdianingseh  , Nisa Fauziyatun , Ain Hurun , Machmudah
Published: September 2024

The leading cause of mortality after infection and hemorrhage is preeclampsia. Preeclampsia can develop in a pregnant woman anywhere from the third trimester onwards, or after the 20th week of gestation. Finding out how self-management affects preeclampsia in pregnant women was the goal of this study at RSI Jemursari Surabaya. This study's pre-experimental design makes use of the One-Group Pre-Test and Post-Test methodology. The study's population consisted of sixty-two pregnant women diagnosed with preeclampsia at RSI Jemursari Surabaya. extracted with the use of a sequential non-random sampling procedure. One variable that may be controlled is preeclampsia, while another is self-management. The device used a preeclampsia observation sheet. In order to analyze the data, the Wilcoxon ranks test statistic was used, with a significance threshold of = 0.05. The results obtained from 53 respondents that before being given intervention there were severe preeclampsia (39.6%), mild preeclampsia (49.1%) of respondents, and superimposed (11.3%). 0%), mild preeclampsia (71.7%) and superimposed preeclampsia (11.3%). Analysis of the Wilcoxon ranks test statistical test obtained a significance value of P=0.001 so that H0 is rejected and H1 is accepted. Self Management has an effect on the incidence of preeclampsia, so pregnant women can do it independently and nurses are expected to be able to provide education in health services.
IoT and Machine Learning Based Attacks Detection Model on Wearable Health Care Devices
Authors: Rahman Dr. F , Lalnunthari
Published: September 2024

The Internet of Things (IoT) in healthcare is becoming more and more popular in the field of research aimed at improving the effectiveness of intelligent healthcare networks and applications. Nonetheless, distinct risks affect the security and privacy of data in smart health (S-Health). IoT enables healthcare professionals to engage with patients more proactively and with greater vigilance. Smart gadgets with tiny sensors attached to them that communicate with one another to track each other's performance are part of the Internet of Things. To defend S-Health from MITM attacks. The suggested method employs two layers of machine learning algorithms for attack detection and security mechanisms, including low-cost access policies for SHRs (Smart Health Records), lightweight IoT detection schemes, and timely detection of to lessen their impact on the network. According to simulation data, the suggested Hybrid ML performs better than current methods and has a higher attack detection rate overall. The main goal of this research article is to develop an attack detection technique.
Significance of Machine Learning Algorithms to Improve Predictive Analytics in Chronic Disease Management through Pharmacogenomics
Authors: Bharti Gopesh Kumar , Jaikumar Deshmukh Vaishnavi
Published: September 2024

The treatment of chronic diseases is an important concern in global health. Machine learning (ML)-based disease prediction models are becoming more important for making informed medical decisions in light of the paradigm shift towards preventative care. Integrating genetic, pharmacogenomic, personal health, and psychosocial data can greatly assist healthcare practitioners in making treatment-related decisions for patients with chronic diseases. This study utilizes a Deep Convolutional Neural Network-assisted Chronic Disease Management (DCNN-CDM) through pharmacogenomics and an improved predictive analytics model to enable informed real-time decision-making at the point of care. Data augmentation in terms of feature space allows the DCNN model to avoid over-fitting while effectively capturing high-level features submerged in chronic disease datasets. Afterwards, this work suggests an attention-empowered DCNN model to enhance sick case diagnosis accuracy, which augments data regarding sample space, thereby alleviating the class imbalance issue. Electronic health information data mining is now using predictive analytics to determine individuals at risk of acquiring chronic disease problems. The suggested model may aid in the early and accurate diagnosis of chronic diseases. The numerical outcomes demonstrate that the recommended DCNN-CDM model increases the accuracy rate of 98.7%, patient monitoring rate of 97.5%, F1-score rate of 96.3% and predictive performance rate of 95.1% compared to other existing methodologies.
Prediction of Drinking Water Quality for Effective Public Health Management to Avoid Water Borne Diseases
Authors: Saini Rajvir , Shrivastava Vivek
Published: September 2024

The issue of water quality failure is a persistent global concern that leads to sickness, toxicity, the spread of diseases, and loss of life in metropolitan areas. Various physical, functional, and ecological factors may affect drinking water quality. These concerns include the incursion of pollutants into water pipes, leakage, the formation of disinfectant waste products, the penetration of chemicals or microbes, and pollution. Water-borne Diseases (WD) have emerged as a significant global public health issue. It is imperative to forecast the quality of drinkable water by utilizing an automated model that provides a preventive strategy that may be created to enhance public health management (PHM). This study forecasted the Drinking Water Quality (DWQ) to promote Public Health Management (PHM) strategies to prevent WD. Convolutional Neural Network (CNN) with Inverse Distance Loaded (IDL) interpolation has been used to forecast DWQ. One hundred five water specimens from the research region underwent thorough examination via physiochemical and microbiological analyses. The tested characteristics were pH, turbidity, temperature, fluoride concentration levels, and bacterial counts (Faecal Coliforms) to prevent WD. The test findings indicated that the CNN-IDL projected 35% of water specimens from the domestic pipeline network had bacteria levels below what the WHO considers acceptable. Also, about 57% of the samples from the home pipeline network met the fluoride reference values set by the WHO. The sanitary assessment rating clearly showed that the lack of appropriate measures to protect against multiple barriers resulted in declining water quality for users. The findings of this research will be valuable to administrators in implementing essential strategies to avoid WD before it significantly impacts public health.
Blockchain-Based Secured Drug Traceability in Health Care Application
Authors: Jaleel Dr. Uruj , Lalmawipuii R
Published: September 2024

Despite the enormous advancements in technology, fraudsters continue to attack the healthcare industry. Numerous recent healthcare security breaches indicate that attackers are focussing on the electronic health data and the drug supply chain. Additional investigation into security problems in the healthcare sector demonstrates that the primary cause of these incidents is the centralisation of data storage. The healthcare sector also lacks immutability, adaptability, security, and privacy in addition to having insufficient documentation. It has been discovered that blockchain technology may offer a complete solution to the main issues the healthcare industry is now facing. Healthcare issues may be resolved with the aid of blockchain's intrinsic qualities, which include immutability, transparency, privacy, security, and documentation. In this work, an interactive blockchain 2.0 medication supply chain tracking system is created, and Hyperledger Calliper is used to measure the system's performance. This system makes sure that everyone involved in the drug supply chain can follow the drug's journey from the producer to the end user. The members' own inventory management is also aided by it. In addition to providing privacy and transparency, this method offers a viable remedy for the issues associated with counterfeit drugs. With one ordered peer and one endorsed peer, the system can process 25,000 transactions per second.
Decision Support System Based on Deep Learning with Big Data for Pneumonia Prediction
Authors: Sinha Dr. Anupa , Kumar Yalakala Dinesh
Published: September 2024

A bacterial, viral, or fungal infection of the lungs causes pneumonia in humans. It is the primary cause of global decline. Around 27% of deaths worldwide are attributable to this illness. A World Health Organisation report states that this serious infectious disease claims the lives of almost 2.5 million people annually. Early detection of chest illness, including pneumonia, can reduce the likelihood that the condition will worsen by allowing for the proper course of treatment. Accurate CT scans and CXR (chest X-ray) reports are renowned for being exact methods of diagnosis and prediction. This approach is trustworthy and non-invasive, and it can be used as a screening tool when a disease diagnosis is necessary. Nevertheless, research has demonstrated that even highly trained radiologists regularly fail to correctly identify pneumonia disease in its early stages. The severity of the sickness and the death rate increase as a result of diagnostic delays. Machine learning has affected every aspect of human life in the twenty-first century. It has a significant effect on the medical field in terms of early diagnosis of serious illnesses. Therefore, an intelligent health care system based on artificial intelligence (AI) was presented in this work for the early and accurate diagnosis of pneumonia disease.