bluuebunny/crossref_metadata_2025_split huggingface dataset:
Utilizing injury severity score, Glasgow coma scale, and revised trauma score for trauma-related in-hospital mortality and ICU admission prediction; originated from 7-year results of a nationwide multicenter registry
Authors: Khavandegar Armin , Baigi Vali , Zafarghandi Mohammadreza , Rahimi-Movaghar Vafa , Fakharian Esmaeil , Saeed-Banadaky Seyed Houssein , Hoseinpour Vahid , Sadeghi-Bazargani Homayoun , Zolfaghari Sadrabad Akram , Daliri Salman , Isfahani Mehdi Nasr , Rahmanian Vahid , Hemmat Morteza , Aali Rahim , Kogani Mohamad , Pourmasjedi Sobhan , Piri Seyed Mohammad , Mirzamohamadi Sara , Hassan Zadeh Tabatabaei Mahgol Sadat , Naghdi Khatereh , Salamati Payman 
Published: August 2024

Objective: During the past few decades, many scoring systems have been developed to evaluate the severity of injury and predict the outcome in trauma patients. This study aimed to assess the capacity of three common trauma scoring systems: injury severity score (ISS), Glasgow coma scale (GCS), and revised trauma score (RTS) in predicting in-hospital mortality and ICU admission in patients with traumatic injury.
Methods: This is a multicenter study of the hospital-based national trauma registry of Iran (NTRI), an ongoing registry-based trauma database. This study included trauma cases from 12 major trauma centers throughout the country admitted between July 2016 and November 2023. The inclusion criteria were all patients admitted to the emergency department due to trauma, hospitalized for at least 24 hours, deceased within the first 24 hours of admission, and patients transferred from the intensive care unit (ICU)s of other hospitals.
Results: A total of 50,458 traumatic patients, with 38,740 (76.9%) being male, were included in this study. After adjustment for confounders, head, face, and neck injuries were associated with the highest odds of death (OR: 7.51, P-value<0.001), whereas abdominal injuries were associated with the highest odds of ICU admission (OR: 4.58, P-value<0.001). Each Unit increase in RTS score was accompanied by a 61% decrease in odds of death (OR: 0.39, P-value<0.001). The area under the ROC curve for predicting in-hospital mortality was 0.81 (0.79 to 0.82) in ISS, 0.78 (0.77 to 0.80) in GCS, and 0.75 (0.73 to 0.76) in RTS. There was a significant difference between RTS and GCS, as well as RTS and ISS for in-hospital mortality prediction (P-values< 0.001). The area under the ROC curve for the prediction of ICU admission was 0.75 (0.74 to 0.75) in ISS, 0.63 (0.62 to 0.63) in GCS, and 0.62 (0.61 to 0.63) in RTS. There was a statistically significant difference between ISS and GCS, as well as ISS and RTS, for ICU admission prediction (P-value<0.001).
Conclusion: ISS is the best predictor of in-hospital mortality and ICU admission, compared to GCS and RTS.
Comparison of neutrophil-to-lymphocyte ratio,platelet-to-lymphocyte ratio ,and red blood cell distribution width during the attack phase of familial Mediterranean fever with the silent phase of the disease in patients referred to the emergency department
Authors: Shotorbani Babak Sandoghchian , Ajri-Khamesloo Faramarz , Alizadeh Fatemeh , Mahboobi Leila 
Published: August 2024

Objective: As patients with acute-phase familial Mediterranean fever (FMF) require prompt diagnosis for optimal management, we are conducting a study to compare inflammatory markers during the attack and silent phases in individuals referred to the emergency department.
Methods: This case-control study involved 184 FMF patients under 16 years old, with data collected at Bo Ali Hospital's emergency department in Ardabil city throughout 2022. Patients in the attack phase were assessed by emergency medicine specialists, while those in the silent phase were recruited from the rheumatology clinic. Hematological parameters were obtained from venous blood samples, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and red blood cell distribution width (RDW) were calculated. Statistical analyses included 1-Sample Kolmogorov-Smirnov, ANOVA, Tukey's-b post hoc, Independent Samples T-test, Kruskal-Wallis, and Pearson Chi-squared tests.
Results: In the attack group, the NLR correlated with increased leukocytes (r=0.652, P<0.001) and RDW (r=0.310, P=0.003). The non-attack group showed a correlation between the NLR and higher leukocytes (r=0.384, P<0.001) and ESR (r=0.214, P=0.04). Additionally, the attack group exhibited a correlation between the PLR and higher leukocytes (r=0.711, P=0.009), and ESR (r=0.285, P=0.014) while no correlation was found in the non-attack group.
Conclusion: Our study revealed that RDW levels were significantly higher in FMF patients, indicating clinical inflammation. During FMF attacks, NLR and PLR ratios were notably elevated, making them key markers for systemic inflammation in these patients.
APPLICATION OF DISCOVERY LEARNING LEARNING MODEL IN IMPROVING ENGLISH LEARNING OUTCOMES IN GRADE VIII B STUDENTS OF MTS ISLAMIYAH SUKOPURO
Authors: Krisnawati Krisnawati 
Published: August 2024

The purpose of this study was to determine whether there was a student response of the effect of the application of the Discovery Learning models in improving English learning outcomes in the daily test of class VIII B MTs Islamiyah Sukopuro. This type of search in classroom action research which is conducted face-to-face {offline} in the classroom. The subjects of this study were class students VIII B Islamiyah Sukopuro add smester for the academic year 2022-2023. The object of this research is the results of daily tests. This study uses two cycles to improve the abilityto analyze the results of daily tests through four stages of activities, namely planning, action, evaluation, and reflection. The collection technique in this study used the test and observation method. The results showed that {1} the application of the Discovery Learning model was able to improve students’ ability to understand the material. { 2}the results of students responses to the application of the Discovery Learning model were quite successful, especially when viewed from the results of daily tests in understanding the material.
Lateral Wall Integrity of the Greater Tuberosity Is Important for the Stability of Osteoporotic Proximal Humeral Fractures After Plate Fixation
Authors: Kim Dohyun , Lim Joon-Ryul , Yoon Tae-Hwan , Shin Seung-Hwan , Chun Yong-Min 
Published: August 2024

Background:
Previous studies assessing surgical fixation of osteoporotic proximal humeral fractures have primarily focused on medial calcar support. In this study, we utilized a specific model for 2-part surgical neck fracture of the osteoporotic proximal humerus to investigate how severe comminution of the greater tuberosity (GT) lateral wall affects biomechanical stability after fixation with a plate.

Methods:
Ten matched pairs of cadaveric humeri (right and left) were assigned to either a surgical neck fracture alone (the SN group) or a surgical neck fracture with GT lateral wall comminution (the LW group) with use of block randomization. We removed 5 mm of the lateral wall of the GT to simulate severe comminution of the lateral wall. Axial compression stiffness, torsional stiffness, varus bending stiffness, and the single load to failure in varus bending were measured for all plate-bone constructs.

Results:
Compared with the SN group, the LW group showed a significant decrease in all measures, including torsional stiffness (internal, p = 0.007; external, p = 0.007), axial compression stiffness (p = 0.002), and varus bending stiffness (p = 0.007). In addition, the mean single load to failure in varus bending for the LW group was 62% lower than that for the SN group (p = 0.005).

Conclusions:
Severe comminution of the GT lateral wall significantly compromised the biomechanical stability of osteoporotic, comminuted humeral surgical neck fractures.

Clinical Relevance:
Although the generalizability of this cadaveric model may be limited to the extreme clinical scenario, the model showed that severe comminution of the GT lateral wall significantly compromised the stability of osteoporotic humeral surgical neck fractures fixed with a plate and screws alone.
Optimizing ChatGPT for scientific writing in the digital age
Authors: Pratiwi Noor Komari , Yulianto Bambang , Mintowati Mintowati , Sodiq Syamsul 
Published: August 2024

The emergence of advanced artificial intelligence-based machines such as ChatGPT has brought about changes in the scientific writing process, especially among students. Aspects of originality, creativity, and quality of writing results in the scientific writing process need to be studied to maintain academic integrity, open up opportunities for idea development, and produce coherent and structured writing. This study aims to analyze the use of ChatGPT as a tool in the process of scientific writing in Indonesian, especially in writing the background of the problem for the preparation of the final project of Informatics Engineering study program students. This research is a descriptive qualitative research with content analysis approach. Sampling was done by purposive sampling technique. Sampling was done by purposive sampling technique. A total of 18 students of class R67 in semester VI of the Informatics Engineering study program, Indraprasta PGRI University Jakarta were selected because they routinely use ChatGPT in working on scientific writing assignments. Data was collected by reviewing documents in the form of the results of the task of writing the background of the problem made by students using ChatGPT as a tool in the Scientific Writing course. The use of ChatGPT in scientific writing offers significant benefits in terms of creativity and writing quality. The results show that this technology can make learning more efficient by creating new concepts and improving understanding of research ideas. In addition, ChatGPT also helps to produce quality writing. However, ethical issues related to academic integrity should be considered by analyzing the originality aspect through similarity check with turnitin application. Therefore, while ChatGPT provides many benefits in improving the academic writing process, it is imperative to balance these benefits with careful attention to ethical considerations to maintain academic integrity.
Machine Learning–Based Prediction for High Health Care Utilizers by Using a Multi-Institutional Diabetes Registry: Model Training and Evaluation
Authors: Tan Joshua Kuan , Quan Le , Salim Nur Nasyitah Mohamed , Tan Jen Hong , Goh Su-Yen , Thumboo Julian , Bee Yong Mong 
Published: August 2024

Background
The cost of health care in many countries is increasing rapidly. There is a growing interest in using machine learning for predicting high health care utilizers for population health initiatives. Previous studies have focused on individuals who contribute to the highest financial burden. However, this group is small and represents a limited opportunity for long-term cost reduction.

Objective
We developed a collection of models that predict future health care utilization at various thresholds.

Methods
We utilized data from a multi-institutional diabetes database from the year 2019 to develop binary classification models. These models predict health care utilization in the subsequent year across 6 different outcomes: patients having a length of stay of ≥7, ≥14, and ≥30 days and emergency department attendance of ≥3, ≥5, and ≥10 visits. To address class imbalance, random and synthetic minority oversampling techniques were employed. The models were then applied to unseen data from 2020 and 2021 to predict health care utilization in the following year. A portfolio of performance metrics, with priority on area under the receiver operating characteristic curve, sensitivity, and positive predictive value, was used for comparison. Explainability analyses were conducted on the best performing models.

Results
When trained with random oversampling, 4 models, that is, logistic regression, multivariate adaptive regression splines, boosted trees, and multilayer perceptron consistently achieved high area under the receiver operating characteristic curve (>0.80) and sensitivity (>0.60) across training-validation and test data sets. Correcting for class imbalance proved critical for model performance. Important predictors for all outcomes included age, number of emergency department visits in the present year, chronic kidney disease stage, inpatient bed days in the present year, and mean hemoglobin A1c levels. Explainability analyses using partial dependence plots demonstrated that for the best performing models, the learned patterns were consistent with real-world knowledge, thereby supporting the validity of the models.

Conclusions
We successfully developed machine learning models capable of predicting high service level utilization with strong performance and valid explainability. These models can be integrated into wider diabetes-related population health initiatives.
Predicting Falls in the Nursing Homes via Recurrent Neural Network Models
Authors: Kravchenko Olga V , Jin Peng , Shan Xiaoyue , Perez Eddie , Munro Paul , Boyce Richard D 
Published: August 2024

Background This study aimed to develop RNN algorithms to predict falls in nursing homes. Methods The MDS dataset and prescription drug exposure records were utilized to train RNN, LSTM, and GRU models for predicting falls within 90 days window. Results were compared to the previously evaluated CART-logit model. A ϕK correlation coefficient was used for feature analysis. Results RNNs performed similarly (AUROC ≈ 0.74). Feature analysis identified significant correlations for the delirium scale (ϕK = 0.63), use of antipsychotic medication (ϕK = 0.54), exposure to psychotropic medication (ϕK = 0.56), and cumulative number of days spent in the facility ( ϕK = 0.54). Conclusions All three models outperformed the CART-logit model, emphasizing significance of incorporating temporal aspects in fall prediction.
Evaluation of automated photograph-cephalogram image integration using artificial intelligence models
Authors: Moon Jun-Ho , Kim Min-Gyu , Cho Sung Joo , Ko Dong-Yub , Hwang Hye-Won , Park Ji-Ae , Lee Shin-Jae 
Published: August 2024

ABSTRACT

Objectives
To develop and evaluate an automated method for combining a digital photograph with a lateral cephalogram.

Materials and Methods
A total of 985 digital photographs were collected and soft tissue landmarks were manually detected. Then 2500 lateral cephalograms were collected, and corresponding soft tissue landmarks were manually detected. Using the images and landmark identification information, two different artificial intelligence (AI) models—one for detecting soft tissue on photographs and the other for identifying soft tissue on cephalograms—were developed using different deep-learning algorithms. The digital photographs were rotated, scaled, and shifted to minimize the squared sum of distances between the soft tissue landmarks identified by the two different AI models. As a validation process, eight soft tissue landmarks were selected on digital photographs and lateral cephalometric radiographs from 100 additionally collected validation subjects. Paired t-tests were used to compare the accuracy of measures obtained between the automated and manual image integration methods.

Results
The validation results showed statistically significant differences between the automated and manual methods on the upper lip and soft tissue B point. Otherwise, no statistically significant difference was found.

Conclusions
Automated photograph-cephalogram image integration using AI models seemed to be as reliable as manual superimposition procedures.
Comparison of the effect of clear twin block and traditional twin block on speech: a randomized clinical trial
Authors: Shahbodaghi Mohammad Rahim , Zali Mahsa , Behroozian Ahmad , Dadgar Hooshang 
Published: August 2024

ABSTRACT

Objectives
To compare the effect of clear twin block (CTB) and traditional twin block (TTB) appliances on speech.

Materials and Methods
In this randomized clinical trial, 18 skeletal Class II (Class II, division 1) growing patients were selected and randomly divided into CTB and TTB groups. Objective and semiobjective speech assessment tests were performed for vowel and consonant analyses at four time intervals: before (T0), immediately after (T1), 1 month after (T2), and 3 months after (T3) inserting the appliance. Data were analyzed using analysis of variance and independent t-test at the .05 significance level.

Results
Intergroup comparisons showed that the CTB group had less speech distortion immediately after insertion of the appliance (P &lt; .05) than the TTB group; however, the differences were not significant at other time intervals. Intragroup comparisons showed that the number of distortions decreased significantly from T1 to T3 in both groups (P &lt; .05). In contrast to CTB, the T0–T3 comparison was significant in the TTB group.

Conclusions
Although both appliances had some effects on speech, CTB had less speech distortion immediately after insertion, which is a very crucial moment in patient compliance. Additionally, articulation structures adapted to CTB faster than to TTB.
More molar distal movement than pretreatment cone-beam computed tomography posterior space available at the root level in mandibular dentition distalization with microimplants
Authors: Sun Di , Kim Ho-Jin , Noh Hyung-Kyu , Park Hyo-Sang 
Published: August 2024

ABSTRACT

Objectives
To compare the mandibular posterior space available before treatment and the distance of molar distalization achieved after mandibular dentition distalization with microimplants.

Materials and Methods
A total of 66 Class I or III adult patients (mean age = 24.46 ± 4.89 years) who underwent molar distalization using microimplants were retrospectively included. The posterior space available distal to the second molar before treatment and the distance of distalization achieved after treatment were measured using axial cone-beam computed tomography images (0, 2, 4, and 6 mm apical to the second molar root furcation). Changes in lingual cortical thickness and molar root length after treatment were examined. Paired t-test or Wilcoxon signed-rank test was performed to compare measurements before and after treatment. Spearman correlation analysis was performed to assess the relationship between thinning of the cortical plate and root resorption.

Results
Achieved distalization distance was significantly greater than pretreatment posterior space available by 0.8 mm at all root levels (P &lt; .001). The difference was greater toward the root apex level and greater in the Class III group than the Class I group. Lingual cortical thickness was significantly decreased after treatment along with resorption of the second molar distal root (P &lt; .001). In addition, a positive correlation was found between thinning of the cortical plate and distal root resorption of the molar (P &lt; .001).

Conclusions
Achieved distalization distance of the mandibular molar using microimplants was greater than the pretreatment posterior space available. Thinning of the lingual cortex and root resorption were observed after distalization.
Study on the Interaction between Media and Chinese Traditional Theater Culture Industry
Authors: Wang Lixue 
Published: August 2024

Abstract
In the information age, the interaction between media and the cultural industry has gradually become a hot spot for academic research. The traditional Chinese theatre culture industry has become a significant area of research on cultural heritage and innovation, seeking development and innovation while considering the impact and opportunities of new media. This study explores how the media influences the development of the Chinese traditional theatre and culture industries and how they mutually promote and deeply integrate. The study systematically analyses the mode and effect of the interaction between the two using a combination of principal component analysis and the DEA evaluation model, combined with a particle swarm algorithm-optimised BP neural network prediction model. We found that during 2018– 2022, the total amount of broadcasting of Huangmei Opera reached 2.97 billion through the media platform, demonstrating the great promotion of the media for disseminating traditional theatre culture. The interaction between the media and the theatre culture industry enhances theatre’s market share and promotes cultural diversification. This paper explores the close relationship between the media and the Chinese traditional theatre culture industry, which is crucial in promoting the development of the culture industry.
Observability analysis of distribution networks based on robust greedy algorithm
Authors: Chong Wang , Hui Zhang , Hongbin Liu , Jian Li , Yougang Ren 
Published: August 2024

Abstract
In this paper, a robust greedy algorithm is applied to select the node with the highest weight value for fault observation in distribution networks. Except for the first observation node, the weights of the remaining nodes are calculated based on the results of the last observation node. The scheduling cycle is divided into several consecutive periods, and the network operation structure is observed for each period, which is gradually merged to finally obtain a set of solution schemes that satisfy the constraints on the number of switching actions for dynamic reconfiguration collaboration. The results show that the line fault system measurability is all in the 81.8%-100% interval. The method in this paper can directly locate 64.3% of the line faults in the 10kV distribution network, which can significantly reduce the number of traveling wave-locating devices, lower the investment cost, and reduce the fault locating error. It has a certain degree of adaptability in the case of the line N-1. Network operation observation can be found that the highest load-interval in a day is from 5:00 to 18:00. Using the method of this paper reduces 1 division period compared with the traditional method, reconfigures the structure to reduce the number of switching actions, and reduces the network loss from 812.06kW·h to 805.69kW·h.
Mutual Influence Mechanism and Optimization Strategy of University Town and Urban Economic Growth Based on Time Series Forecasting Model
Authors: Jiang Yihuo , Lan Fuji 
Published: August 2024

Abstract
University towns and urban economic growth have important interactions, and time series forecasting models can enable urban planners to better clarify the relationship between the two so as to make more scientific and reasonable decisions. Based on the time series forecasting model constructed in this paper, this paper analyzes and forecasts the relationship between university cities and urban economic growth in C. The main conclusions of this paper are that the p-value of ARIMA(0,2,3) and ARIMA(1,1,1) models is lower than 0.05, and the prediction accuracy of ARIMA(1,1,1) model is higher than that of ARIMA(0,2,3) and ARIMA(1,1,1) model in the prediction of the two. ARIMA(0,2,3) with predicted values of 27631.3, 31541.5, and 24412.45, and the error values from the actual values are only 304.98, 1997.49, and 867.95. This paper’s time series prediction model has achieved good results, as evidenced by this. Y1 shows a highly positive correlation with X1, X3, and X4 and a significant positive correlation with X2, which leads to the conclusion that the total amount of investment in urban construction of the university city of C city has a substantial relationship with the economic growth of C city.