Using Life’s Essential 8 and heavy metal exposure to determine infertility risk in American women: a machine learning prediction model based on the SHAP method by Xiaoqing Gu, Qianbing Li, Xiangfei Wang

“…SHAP analysis showed that LE8, body mass index (“BMI”), diet, Cadmium (“Cd”), Cesium (“Cs”), Molybdenum (“Mo”), Antimony (“Sb”), Tin (“Sn”), education level and pregnancy history were significantly associated with the risk of female infertility. …”
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Construction of a machine learning-based risk prediction model for depression in middle-aged and elderly patients with cardiovascular metabolic diseases in China: a longitudinal st... by Gege Zhang, Sijie Dong, Li Wang

“…LASSO regression was used to screen for risk factors, and three machine learning algorithms—logistic regression (LR), random forest (RF), and XGBoost—were employed to build predictive models. …”
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Spatial and temporal distribution patterns and factors influencing hepatitis B in China: a geo-epidemiological study by Kang Fang, Na Cheng, Chuang Nie, Wentao Song, Yunkang Zhao, Jie Pan, Qi Yin, Jiwei Zheng, Qinglin Chen, Tianxin Xiang

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Recommendations for All-Round Newborns and Infants Hearing Screening in Russian Federation by S. S. Chibisova, G. S. Tufatulin, L. S. Namazova-Baranova, I. V. Koroleva, E. R. Tsygankova, T. G. Markova, N. N. Volodin, G. A. Tavartkiladze

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Drug related problems and associated factors among thyroid disorder patients in Northwest Ethiopia by Fisseha Nigussie Dagnew, Samuel Agegnew Wondm, Melak Erara Mengistu, Samuel Berihun Dagnew, Tilaye Arega Moges, Gashaw Binega Mekonnen

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Association of weight-adjusted waist index and body mass index with chronic low back pain in American adults: a retrospective cohort study and predictive model development based on... by Weiye Zhang, Weiye Zhang, Yan Li, Pengwei Shao, Yuxuan Du, Ke Zhao, Jiawen Zhan, Lee A. Tan

“…Six machine learning algorithms were employed to predict CLBP occurrence and identify the optimal algorithm.ResultsA total of 4,687 participants were included. …”
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Spatio-Temporal Joint Planning for Integrated Energy Systems with Internet Data Center Considering Privacy Preservation by WU Chengbang, CHENG Zhijiang, LU Haifeng, YANG Handi

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Scoring model for exploring factors influencing mortality in dengue patients at a tertiary care hospital: a retrospective study by Abhishek S. Rao, B. H. Karthik Pai, K. Adithi, Lakshmi Belur Keshav, Karan Malhotra, Sneha Nayak, H. K. Sachidananda

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Fibrosis-4plus score: a novel machine learning-based tool for screening high-risk varices in compensated cirrhosis (CHESS2004): an international multicenter study by Bingtian Dong, Ruiling He, Shenghong Ju, Yuping Chen, Ivica Grgurevic, Jianzhong Ma, Ying Guo, Huizhen Fan, Qiang Yan, Chuan Liu, Huixiong Xu, Anita Madir, Kristian Podrug, Jia Wang, Linxue Qian, Zhengzi Geng, Shanghao Liu, Tao Ren, Guo Zhang, Kun Wang, Meiqin Su, Fei Chen, Sumei Ma, Liting Zhang, Zhaowei Tong, Yonghe Zhou, Xin Li, Fanbin He, Hui Huan, Wenjuan Wang, Yunxiao Liang, Juan Tang, Fang Ai, Tingyu Wang, Liyun Zheng, Zhongwei Zhao, Jiansong Ji, Wei Liu, Jiaojiao Xu, Bo Liu, Xuemei Wang, Yao Zhang, Qiong Yan, Hui Liu, Xiaomei Chen, Shuhua Zhang, Yihua Wang, Yang Liu, Li Yin, Yanni Liu, Yanqing Huang, Li Bian, Ping An, Xin Zhang, Shaoting Zhang, Jinhua Shao, Xiangman Zhang, Wei Rao, Chaoxue Zhang, Christoph Frank Dietrich, Won Kim, Xiaolong Qi

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Construction of a risk prediction model for occupational noise-induced hearing loss using routine blood and biochemical indicators in Shenzhen, China: a predictive modelling study by Wenting Feng, Wen Zhang, Yan Guo, Naixing Zhang, Liang Zhou, Dafeng Lin, Linlin Chen, Caiping Li, Liuwei Shi, Xiangli Yang, Peimao Li, Dianpeng Wang

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The financial security management model in second-tier banks by A. Z. Nurmagambetova, S. Z. Nurmagambetov, A. G. Mukusheva

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Protocol for nationwide surveillance of Acute Encephalitis Syndrome (AES) in a network of tertiary care hospitals in India by Anoop Velayudhan, Harmanmeet Kaur, Rahul Dhodapkar, Labanya Mukhopadhyay, Rizwan S. Abdulkader, Sabarinathan R, Valsan Philip Verghese, Lalit Dar, Rakesh Lodha, Ravi V, Sam Joy, Pragya Yadav, Amita Jain, Ajanta Sharma, Kaveri K, Sayantan Banerjee, Anitha PM, Manjusree S, Bharti Malhotra, Baijayantimala Mishra, Mala Chhabra, Asim Sarfraz, Bashir Fomda, Mahima Mittal, Manoj Murhekar, Nivedita Gupta

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Designing Multi-Objective Optimization Model of Electricity Market Portfolio for Industrial Consumptions under Uncertainty by Saeed Khalili, Ebrahim Abbasi, Bardia Behnia, Mohammad Amirkhan

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Novel concept for the healthy population influencing factors by Yuhao Shen, Jichao Wang, Lihua Ma, Huizhe Yan

“…In the rapid urbanization process in China, due to reasons such as employment, education, and family reunification, the number of mobile population without registered residence in the local area has increased significantly. …”
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Prevention of Cardiometabolic Syndrome in Children and Adolescents Using Machine Learning and Noninvasive Factors: The CASPIAN-V Study by Hamid Reza Marateb, Mahsa Mansourian, Amirhossein Koochekian, Mehdi Shirzadi, Shadi Zamani, Marjan Mansourian, Miquel Angel Mañanas, Roya Kelishadi

“…We applied the XGBoost algorithm to analyze key noninvasive variables, including self-rated health, sunlight exposure, screen time, consanguinity, healthy and unhealthy dietary habits, discretionary salt and sugar consumption, birthweight, and birth order, father and mother education, oral hygiene behavior, and family history of dyslipidemia, obesity, hypertension, and diabetes using five-fold cross-validation. …”
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A novel stemness-related lncRNA signature predicts prognosis, immune infiltration and drug sensitivity of clear cell renal cell carcinoma by Jia Liu, Lin Yao, Yong Yang, Jinchao Ma, Ruijian You, Ziyi Yu, Peng Du

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Clinical and socioeconomic factors associated with recurrent atrial fibrillation after catheter ablation or antiarrhythmic drug therapy by Jaejin An, PhD, Nisha Bansal, MD, Chengyi Zheng, PhD, Ming-Sum Lee, MD, PhD, Rong Wei, MA, Teresa N. Harrison, SM, Dongjie Fan, MS, Elisha Garcia, MS, Benjamin Lidgard, MD, Leila R. Zelnick, PhD, Daniel E. Singer, MD, Alan S. Go, MD

“…Conclusion: Heart failure, dyslipidemia, obesity, hypertension, reduced estimated glomerular filtration rate, and living in neighborhoods with low educational attainment were associated with higher risk for AF recurrence, emphasizing the importance of identifying and managing modifiable factors in AF.…”
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MAPPING GENERATIVE AI'S ETHICAL ISSUES IN HIGHER EDUCATION: A FELT-GUIDED SYSTEMATIC REVIEW [PEMETAAN ISU ETIKA GENERATIVE AI DI PENDIDIKAN TINGGI: TINJAUAN SISTEMATIS BERPANDUAN... by okky barus, Achmad Nizar Hidayanto, Imairi Eitiveni

“…The SLR revealed seven prominent ethical concerns: (1) academic integrity and plagiarism, highlighting issues of unauthorized assistance and false authorship; (2) bias and fairness, manifested through algorithmic and linguistic biases; (3) data privacy and security, concerning unauthorized access and re-identification risks; (4) impact on critical thinking and learning outcomes, fostering over-reliance; (5) authorship, intellectual property, and copyright ambiguities; (6) misinformation, hallucinations, and deepfakes, eroding trust; and (7) broader environmental and labor impacts. …”
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Ethical Considerations in Emotion Recognition Research by Darlene Barker, Mukesh Kumar Reddy Tippireddy, Ali Farhan, Bilal Ahmed

“…The paper integrates findings from literature review and initial emotion-recognition studies to create a conceptual framework that prioritizes data dignity, algorithmic accountability, and user agency and presents a conceptual framework that addresses these risks and includes safeguards for participants’ emotional well-being. …”
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Can heart rate sequences from wearable devices predict day-long mental states in higher education students: a signal processing and machine learning case study at a UK university by Tianhua Chen

“…Abstract The mental health of students in higher education has been a growing concern, with increasing evidence pointing to heightened risks of developing mental health condition. …”
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