Improving stroke risk prediction by integrating XGBoost, optimized principal component analysis, and explainable artificial intelligence by Lesia Mochurad, Viktoriia Babii, Yuliia Boliubash, Yulianna Mochurad

“…BMC Medical Informatics and Decision Making…”
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Decision experiences in joint replacement surgery for patients with haemophilic arthritis: A qualitative study by YaNan Kan, YunChun Bao, Fuying Ye

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Sharing reliable information worldwide: healthcare strategies based on artificial intelligence need external validation. Position paper by F. Pennestrì, F. Cabitza, N. Picerno, G. Banfi

“…BMC Medical Informatics and Decision Making…”
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Patients’ and plastic surgeons’ experiences with an online patient decision aid for breast reconstruction: considerations for nationwide implementation by Jacqueline A. ter Stege, Ellen G. Engelhardt, Leonie A.E. Woerdeman, Hester S.A. Oldenburg, Jacobien M. Kieffer, Daniela E.E. Hahn, Frederieke H. van Duijnhoven, Martine A. van Huizum, Regina The, Klemens Karssen, Marianne Kuenen, Miranda A. Gerritsma, Quinten (PQ) Ruhe, Irene S. Krabbe-Timmerman, Martijne van’t Riet, Nikola (AN) Kimmings, Eveline M.L. Corten, Kerry A. Sherman, Arjen J. Witkamp, Eveline M.A. Bleiker

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A machine learning-based model for predicting paroxysmal and persistent atrial fibrillation based on EHR by Yuqi Zhang, Sijin Li, Peibiao Mai, Yanqi Yang, Niansang Luo, Chao Tong, Kuan Zeng, Kun Zhang

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Causal machine learning models for predicting low birth weight in midwife-led continuity care intervention in North Shoa Zone, Ethiopia by Wudneh Ketema Moges, Awoke Seyoum Tegegne, Aweke A. Mitku, Esubalew Tesfahun, Solomon Hailemeskel

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Unlocking the link: predicting cardiovascular disease risk with a focus on airflow obstruction using machine learning by Xiyu Cao, Jianli Ma, Xiaoyi He, Yufei Liu, Yang Yang, Yaqi Wang, Chuantao Zhang

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Examining inclusivity: the use of AI and diverse populations in health and social care: a systematic review by John Gabriel O. Marko, Ciprian Daniel Neagu, P. B. Anand

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Ontology-based expansion of virtual gene panels to improve diagnostic efficiency for rare genetic diseases by Jaemoon Shin, Toyofumi Fujiwara, Hirotomo Saitsu, Atsuko Yamaguchi

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Accounting for racial bias and social determinants of health in a model of hypertension control by Yang Hu, Nicholas Cordella, Rebecca G. Mishuris, Ioannis Ch. Paschalidis

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Developing clinical prognostic models to predict graft survival after renal transplantation: comparison of statistical and machine learning models by Getahun Mulugeta, Temesgen Zewotir, Awoke Seyoum Tegegne, Mahteme Bekele Muleta, Leja Hamza Juhar

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Development of an artificial intelligence-based application for the diagnosis of sarcopenia: a retrospective cohort study using the health examination dataset by Chang-Won Jeong, Dong-Wook Lim, Si-Hyeong Noh, Sung Hyun Lee, Chul Park

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Safety and accuracy of digitally supported primary and secondary urgent care telephone triage in England: an observational study using routine data by Vanashree Sexton, Catherine Grimley, Jeremy Dale, Helen Atherton, Gary Abel

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Healthcare trajectories of aging individuals during their last year of life: application of process mining methods to administrative health databases by Delphine Bosson-Rieutort, Alexandra Langford-Avelar, Juliette Duc, Benjamin Dalmas

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Exploration of the optimal deep learning model for english-Japanese machine translation of medical device adverse event terminology by Ayako Yagahara, Masahito Uesugi, Hideto Yokoi

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APPLICATION OF INTERNAL FINANCIAL STATEMENTS IN BUDGETARY USER MANAGEMENT IN CROATIA by Vesna Vašiček, Verica Budimir, Mirjana Hladika

“…Initial hypothesis of the paper is that the internal financial statements in the Croatian public sector are underdeveloped and insufficiently used in decision making and budgetary user management. By applying the survey method, this paper aims at investigating the current level of using external and internal financial statements in decision making and management of Croatian budgetary users. …”
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APPLICATION OF INTERNAL FINANCIAL STATEMENTS IN BUDGETARY USER MANAGEMENT IN CROATIA by Vesna Vašiček, Verica Budimir, Mirjana Hladika

“…Initial hypothesis of the paper is that the internal financial statements in the Croatian public sector are underdeveloped and insufficiently used in decision making and budgetary user management. By applying the survey method, this paper aims at investigating the current level of using external and internal financial statements in decision making and management of Croatian budgetary users. …”
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Sensation seeking and risk adjustment: the role of reward sensitivity in dynamic risky decisions by Yin Qianlan, Chen Shou, Hou Tianya, Dong Wei, Taosheng Liu

“…By integrating the reinforcement learning model and neural measures obtained from dynamic risk-taking tasks, we aim to explore how these personality traits influence individual decision-making processes and engagement in risk-related activities. …”
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