Machine-learning prediction for hospital length of stay using a French medico-administrative database by Franck Jaotombo, Vanessa Pauly, Guillaume Fond, Veronica Orleans, Pascal Auquier, Badih Ghattas, Laurent Boyer

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Implication of Exclusive Breastfeeding in Early Childhood Dental Disorders: Large Cohort Evidence, US National Survey of Children Health by Laurens Holmes, Janille Williams, Neyha Thompson, Valescia John, Kerti Depeika, Benjamin Ogundele, Michael Enwere

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Magnitude of atopic dermatitis and associated factors among children in northwest Ethiopia by Alemu Bezabih Tegegnie, Yefiru Andualem Mitiku, Biresaw Wassihun Alemu, Yitbarek Genetu Wollie, Tamiru Alene

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The effect of body mass index on maternal and neonatal health in term pregnancies: a cross-sectional study in Turkey by Ayşe Daştan Yilmaz, Kıymet Yeşilçiçek Çalik, Mehtap Budak

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Exploring Long Covid Prevalence and Patient Uncertainty by Sociodemographic Characteristics Using GP Patient Survey Data by Mirembe Woodrow, Nida Ziauddeen, Dianna Smith, Nisreen A. Alwan

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Personalized diagnosis of radiation pneumonitis in breast cancer patients based on radiomics by Xiaobo Wen, Xiaobo Wen, Xiaobo Wen, Yutao Zhao, Wen Dong, Congbo Yang, Jinzhi Li, Li Sun, Yutao Xiu, Chang’e Gao, Ming Zhang

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Leveraging large language models for automated detection of velopharyngeal dysfunction in patients with cleft palate by Myranda Uselton Shirk, Catherine Dang, Jaewoo Cho, Hanlin Chen, Lily Hofstetter, Jack Bijur, Claiborne Lucas, Andrew James, Ricardo-Torres Guzman, Andrea Hiller, Noah Alter, Amy Stone, Maria Powell, Matthew E. Pontell, Matthew E. Pontell

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Diabetic patients’ behaviors and influential factors of using medical and preventative integrated services in Shandong Province: A questionnaire survey by Wenyu Fan, Xia Feng, Xingli Ma, Shilong Zhang, Xindan Zhang, Yang Zhao, Haipeng Wang

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The glycemic index diets and the risk of metabolic syndrome in male urban population of Novosibirsk (population studies) by A. K. Kuntsevich, G. I. Simonova, S. V. Mustafina, E. G. Verevkin, I. P. Berezovikova, P. E. Vloshchinskij, O. D. Rymar

“…The average glycemic index diets (M ± SD) in men Novosibirsk averaged 55,2 ± 3,3, the minimum value of the first quartile – 50,8 ± 2,4 and a maximum value in the fourth – 58,9 ± 1,3. …”
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Evidence-based practice utilization and associated factors among nurses in the emergency department of selected public hospitals, Addis Ababa, Ethiopia, 2024: cross-sectional study by Mekuanint Kassie, Achamyelesh Tadele, Lemlem Beza, Ousman Adal, Aklilu Azazh

“…A lottery method of simple random sampling was used to select 233 participants from 542 nurses registered in the nurse manager office. …”
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Effect of Attending Pregnant Mothers Conference on Birth Preparedness and Complication Readiness Practice among Recently Delivered Women in Rural Libo Kemkem District, North West,... by Melash Belachew Asresie, Dereje Berhanu Abitew, Habtamu Wondiye Bekele, Tadesse Dagget Tesfaye

“…Descriptive, binary, and multiple logistic regression analysis was done. …”
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Generating a Strong Key for a Stream Cipher Systems Based on Permutation Networks by Baghdad Science Journal

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Adverse childhood and school experiences: a retrospective cross-sectional study examining their associations with health-related behaviours and mental health by Karen Hughes, Mark A Bellis, Kat Ford, Catherine A Sharp, Joanne Hopkins, Rebecca Hill, Katie Cresswell

“…Methods A national cross-sectional household survey (N = 1,868 aged 18+) was undertaken in Wales using random quota sampling (November 2022 to March 2023). …”
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Routine Laboratory Markers-Based Machine Learning Model for Predicting Severe Kawasaki Disease in Pediatric Patients by Wu M, Chen J, Gao Y, Chen H, Li W

“…In our comparative analysis of predictive models, the Gradient Boosting model (AUC 0.952) emerged as the most accurate, followed closely by Ada Boost (AUC 0.945), Random Forest (AUC 0.944), CatBoost (AUC 0.957), and Naive Bayes (AUC 0.951). …”
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Developing Machine-Learning Models to Predict Bacteremia in Febrile Adults Presenting to the Emergency Department: A Retrospective Cohort Study from a Large Center by Chia-Ming Fu, Ike Ngo, Pak Sheung Lau, Yaroslav Ivanchuk, Fan-Ya Chou, Chih-Hung Wang, Chien-Yu Lin, Chu-Lin Tsai, Shey-Ying Chen, Tsung-Chien Lu, Hung-Yu Wei

“…Bacteremia was identified in 5,831 (12.1%) and 3,824 (11.9%) cases of the training/validation set and test set, respectively. …”
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Job burnout among public health practitioners in urban China: insights from the post-COVID-19 pandemic context by Ping Xu, Qing Fang, Shasha Yuan, Na Zhang, Danlei Wang, Zhongyue Huang, Min Xian

“…Job burnout was assessed with Chinese revised version of the Maslach Burnout Inventory-General Survey. Binary logistic regression analysis was employed to identify factors influencing job burnout among participants. …”
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Prevalence of anemia and its associated factors among female university students in Jashore, Bangladesh by Farjana Fardaus, Md. Nowshad Mahmud Choyon, Md. Sakhawot Hossain, Md. Obydullah, Farjana Khatun, Md. Hasibul Hasan Milton, Fakir Md. Shah Hafiz, Tanvir Ahmad

“…Methods A cross-sectional study was conducted from November 2023 to March 2024 among 401 randomly selected female students (18–28 years) at Jashore University of Science and Technology who did not report any known chronic illnesses or visible signs of acute illness at the time of data collection. …”
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Development and evaluation of a dynamic nomogram model for intraoperative blood transfusion decision-making by Min Li, Wei Jiang, Jialing Lin, Hui Du, Jiawen Shan, Li Qin

“…In the training set, independent risk factors affecting intraoperative blood transfusion in patients were obtained through Lasso regression and binary logistic regression analysis, and the regression model was established and validated.ResultsThrough Lasso regression with cross-validation and binary logistic regression analysis, the independent risk factors affecting patients’ intraoperative blood transfusion decision-making were determined as ASAs (III) (OR = 3.009, 95% CI = 1.311–6.909), surgical grading (IV) (OR = 3.772, 95% CI = 1.112–12.789), EBL (OR = 1.003, 95% CI = 1.002–1.004), preHGB (OR = 0.932, 95% CI = 0.919–0.946), LVEF (OR = 1.063, 95% CI = 1.028–1.098), Temp (OR = 57.14, 95% CI = 9.740–35.204), preAPTT (OR = 1.147, 95% CI = 1.079–1.220), and preDD (OR = 1.127, 95% CI = 1.048–1.212). …”
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Housing Improvements and Malaria Risk in Sub-Saharan Africa: A Multi-Country Analysis of Survey Data. by Lucy S Tusting, Christian Bottomley, Harry Gibson, Immo Kleinschmidt, Andrew J Tatem, Steve W Lindsay, Peter W Gething

“…Individual survey odds ratios (ORs) were combined to determine a summary OR using a random effects meta-analysis. Of 284,532 total children surveyed, 139,318 were tested for malaria infection using microscopy (n = 131,652) or RDT (n = 138,540). …”
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Prevalence and associated factors of adherence to antihypertensive medication: a nationwide cross-sectional study by Muhammad Arshed, Mehwish Kiran, Muhammad Farooq Umer, Jamil Adnan Samkari, Syed Mehmood ul hassan, Shafqat Qamer, Ali Hassan Gillani, Sajid Hameed, Waseela Ashraf, Hasan Mujtaba, Muhammad Naseem Khan

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