Sarcopenia, Depressive Symptoms, and Fall Risk: Insights from a National Cohort Study in the Chinese Population by Zhang X, Ye D, Dou Q, Xie F, Zeng R, Zhu K, Zhu W, Zhu A, Chen L, Wu Y, Fan T, Peng P, Huang Y, Xiao S, Bian J, Shi M, Wang J, Zhang W

“…Xiaoming Zhang,1,* Dongmei Ye,2,* Qingli Dou,1,* Fayi Xie,2 Rui Zeng,2 Ke Zhu,2 Wan Zhu,2 Aizhang Zhu,3,4 Lihuan Chen,5 Yishan Wu,2 Tenghui Fan,2 Pai Peng,2 Yuxu Huang,3,4 Shunrui Xiao,2 Jiahui Bian,2 Mengxia Shi,2 Jiang Wang,3,4 Wenwu Zhang1 1Department of Emergency, The People’s Hospital of Baoan Shenzhen, Shenzhen, Guangdong province, People’s Republic of China; 2School of Clinical Medicine, Jinggangshan University, Ji’an, Jiangxi Province, People’s Republic of China; 3School of Basic Medicine, Jinggangshan University, Ji’an, Jiangxi Province, People’s Republic of China; 4Online Collaborative Research Center for Evidence-Based Medicine Ministry of Education, Jinggangshan University Branch, Ji’an, Jiangxi Province, People’s Republic of China; 5School of Chinese Medicine, Jinggangshan University, Ji’an, Jiangxi Province, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xiaoming Zhang, Department of emergency, The People’s hospital of Baoan Shenzhen, Shenzhen, Guangdong province, People’s Republic of China, Email zhangmuxi0310@163.com Jiang Wang, School of Basic Medicine, Jinggangshan University, Ji’an, Jiangxi Province, People’s Republic of China, Email 9920070082@jgsu.edu.cnBackground: Previous investigations have indicated that both sarcopenia and depressive symptoms are linked to a heightened risk of falls. …”
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Prevalence, types, risk factors and clinical correlates of anaemia in older people in a rural Ugandan population. by Joseph O Mugisha, Kathy Baisley, Gershim Asiki, Janet Seeley, Hannah Kuper

“…HIV status was assessed using an algorithm for HIV rapid testing. Questionnaires were used to collect data on sociodemographic characteristics and other risk factors for anaemia.…”
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Ethical and social issues in prediction of risk of severe mental illness: a scoping review and thematic analysis by Ivars Neiders, Signe Mežinska, Neeltje E. M. van Haren

“…Abstract Background Over the last decade, there has been considerable development in precision psychiatry, especially in the development of novel prediction tools that can be used for early prediction of the risk of developing a severe mental disorder such as schizophrenia, depression, bipolar disorder. …”
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Mortality impact, risks, and benefits of general population screening for ovarian cancer: the UKCTOCS randomised controlled trial by Usha Menon, Aleksandra Gentry-Maharaj, Matthew Burnell, Andy Ryan, Jatinderpal K Kalsi, Naveena Singh, Anne Dawnay, Lesley Fallowfield, Alistair J McGuire, Stuart Campbell, Steven J Skates, Mahesh Parmar, Ian J Jacobs

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Development and validation of a machine learning risk prediction model for asthma attacks in adults in primary care by Holly Tibble, Aziz Sheikh, Athanasios Tsanas

“…Furthermore, it could be used to educate patients about their individual risk and risk factors, and promote healthier lifestyle changes, use of self-management plans, and early emergency care seeking following rapid symptom deterioration.…”
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Exploring the link between the ZJU index and sarcopenia in adults aged 20–59 using NHANES and machine learning by Huan Chen, Ning Du, Hong Xiao, Zhao Wang

“…The association between ZJU and sarcopenia was assessed using multivariable logistic regression, restricted cubic splines (RCS) for smooth curve fitting, and subgroup analyses. To improve risk stratification and identify key predictors, machine learning techniques—including Random Forest, SHAP, and the Boruta algorithm—were applied. …”
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Assessing psychological resilience and its influencing factors in the MSM population by machine learning by Yiwei Zhou, Zejie Zhang, Fanglv Xiang, Minlu Xu, Zumu Zhou

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Explainable Siamese Neural Networks for Detection of High Fall Risk Older Adults in the Community Based on Gait Analysis by Christos Kokkotis, Kyriakos Apostolidis, Dimitrios Menychtas, Ioannis Kansizoglou, Evangeli Karampina, Maria Karageorgopoulou, Athanasios Gkrekidis, Serafeim Moustakidis, Evangelos Karakasis, Erasmia Giannakou, Maria Michalopoulou, Georgios Ch Sirakoulis, Nikolaos Aggelousis

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Optimal by criterion of minimum of average risk adaptive device for decision meaning considering correlation properties of the reflected signal by S. A. Gabets, S. U. Sedushev, R. A. Hutsau

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Development of the predictive model for I stage breast cancer by A. Kh. Ismagilov, A. S. Vanesyan, D. R. Khuzina

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PDP1 related ferroptosis risk signature indicates distinct immune microenvironment and prognosis of breast cancer patients by Yufeng Wang, Huifen Dang, Gongjian Zhu, Yingxia Tian

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Postdigital Bodies: Young People’s Experiences of Algorithmic, Tech-Facilitated Body Shaming and Image-Based Sexual Abuse during and after the COVID-19 Pandemic in England by Jessica Ringrose, Betsy Milne, Tanya Horeck, Kaitlynn Mendes

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The association between cystatin C and hypertension risk in diabetes patients: A multi-cohort cross-sectional study by Ye Kuang, Jia Wang, Yang Wang, Chuanmei Peng, Pei He, Yong Ji, Jinrong Tian, Yong Yuan, Lei Feng

“…A risk prediction model incorporating CysC concentration was developed and adjusted for age, sex, race, education, body mass index, smoking status, and drinking status. …”
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A Virtual Power Plant-Integrated Proactive Voltage Regulation Framework for Urban Distribution Networks: Enhanced Termite Life Cycle Optimization Algorithm and Dynamic Coordination by Yonglin Li, Zhao Liu, Changtao Kan, Rongfei Qiao, Yue Yu, Changgang Li

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Decoding survival in MASLD: the dominant role of metabolic factors by Zhiqiang Jin, Cheng Zeng, Yang Yang, Shan Zhong, Zhi Zhou

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Habit Predicting Higher Education EFL Students’ Intention and Use of AI: A Nexus of UTAUT-2 Model and Metacognition Theory by Shaista Rashid

“…With the emergence of AI technology, its adoption in higher education has become an interesting field for researchers. …”
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The Effect of Family-Centered Empowerment Model Based on Multimedia Education on the Quality of Life of Children Aged 8-12 Years with Thalassemia by Ayoub Mohamadian, Ali Moeini, Mahnaz Sanjari, Zahra Abdullahzade

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Responsible artificial intelligence in public health: a Delphi study on risk communication, community engagement and infodemic management by Keyrellous Adib, David Novillo-Ortiz, Ben Duncan, Daniela Mahl, Mike S Schäfer, Stefan Adrian Voinea, Cristiana Salvi

“…Challenges and risks affect all three components of RCCE-IM equally, with algorithmic bias and privacy breaches being of particular concern. …”
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Predictors of depression among Chinese college students: a machine learning approach by Lin Luo, Junfeng Yuan, Chenghan Wu, Yanling Wang, Rui Zhu, Huilin Xu, Luqin Zhang, Zhongge Zhang

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Development of a neural network-based risk prediction model for mild cognitive impairment in older adults with functional disability by Deyan Liu, Yuge Tian, Min Liu, Shangjian Yang

“…Results The results indicated that residence location, alcohol consumption, life satisfaction, depressive symptoms, and education level are key factors influencing the risk of MCI among older adults with functional disability. …”
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