Predictive Analysis of Stress and Burnout Among Medical Students: Exploring Personal and Environmental Contributors by Qurratulain Mehfooz, Nadia Tufail, Sehar Shamshad Ali, Raheela Subhani, Sehar Amjad, Zertaj Kashif

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The Predictive Power of Students' Metacognition and Perceptions of Instructional Competencies of Instructors on Academic Life Satisfaction by İbrahim Tuncel, Zeynep Ayvaz-tuncel

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Predicting early cessation of exclusive breastfeeding using machine learning techniques. by Freja Marie Nejsum, Rikke Wiingreen, Andreas Kryger Jensen, Ellen Christine Leth Løkkegaard, Bo Mølholm Hansen

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A time series algorithm to predict surgery in neonatal necrotizing enterocolitis by Cheng Cui, Ling Qiu, Ling Li, Fei-Long Chen, Xiao Liu, Huan Sun, Xiao-Chen Liu, Lei Bao, Lu-Quan Li

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Predicting New York Heart Association (NYHA) heart failure classification from medical student notes following simulated patient encounters by Ishan R. Perera, Taylor Daniels, Janella Looney, Kimberly Gittings, Frederic A. Rawlins

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Machine learning for grading prediction and survival analysis in high grade glioma by Xiangzhi Li, Xueqi Huang, Yi Shen, Sihui Yu, Lin Zheng, Yunxiang Cai, Yang Yang, Renyuan Zhang, Lingying Zhu, Enyu Wang

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A Local–Global Graph KAN for Multi‐Class Prediction of PPI by Minghui Liu, Ying Qu

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Cardiac Clarity: Harnessing Machine Learning for Accurate Heart-Disease Prediction by Sujith Santhosh, Krishnaraj Chadaga, R.Vijaya Arjunan, Sandra D'Souza

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Pedestrian Trajectory Prediction Based on Dual Social Graph Attention Network by Xinhai Li, Yong Liang, Zhenhao Yang, Jie Li

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Gravity Predictions in Data-Missing Areas Using Machine Learning Methods by Yubin Liu, Yi Zhang, Qipei Pang, Sulan Liu, Shaobo Li, Xuguo Shi, Shaofeng Bian, Yunlong Wu

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Generative deep learning for predicting ultrahigh lattice thermal conductivity materials by Liben Guo, Yuanbin Liu, Zekun Chen, Hongao Yang, Davide Donadio, Bingyang Cao

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Predictive criteria for the function of the right ventricle of the heart during mechanical bypass of the left ventricle by D. D. Uzunin, S. Yu. Shemakin

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A new algorithm to assess the risk of malignancy in premenopausal patients with pelvic mass by M. S. Katsyuba, R. Sh. Khasanov, T. I. Madzhidov, G. Z. Muratova, G. A. Usmanova, A. F. Akhmetzyanova, A. Rakhimbekova, V. V. Terentyeva, G. R. Fakhrutdinova

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Predicting Diabetic Retinopathy and Nephropathy Complications Using Machine Learning Techniques by D. R. Manjunath, J. J. Lohith, S. Selva Kumar, Abhijit Das

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Personality-Aware Course Recommender System Using Deep Learning for Technical and Vocational Education and Training by Rana Hammad Hassan, Malik Tahir Hassan, Muhammad Shujah Islam Sameem, Muhammad Aasim Rafique

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PREDICTION OF METASTATIC DAMAGE OF REGIONAL LYMPHATIC NODES IN PATIENTS WITH BREAST CANCER by A. Kh. Ismagilov, N. G. Asnina, I. P. Moshurov, G. A. Azarov

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Novel serum biomarker for powerfully predicting pediatric simple febrile seizures by Jinzhi Mei, Chuanze Hu, Fang Sheng, Zhiyu Wang, Wangxiong Hu

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Machine learning for prediction of childhood mental health problems in social care by Ryan Crowley, Katherine Parkin, Emma Rocheteau, Efthalia Massou, Yasmin Friedmann, Ann John, Rachel Sippy, Pietro Liò, Anna Moore

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Evaluating the relative predictive validity of measures of self-referential processing for depressive symptom severity by Ethel Siew Ee Tan, Hong Ming Tan, Kah Vui Fong, Sheryl Yu Xuan Tey, Nikita Rane, Chong Wei Ho, Zhao Yuan Tan, Rachel Jing Min Ong, Chloe Teo, Jerall Yu, Maxine Lee, An Rae Teo, Sin Kee Ong, Xin Ying Lim, Jin Lin Kee, Jussi Keppo, Geoffrey Chern-Yee Tan

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Optimizing Cardiovascular Risk Management in Primary Care Using a Personalized eCoach Solution Enhanced by an Artificial Intelligence–Driven Clinical Prediction Model: Protocol fro... by Rutger van Mierlo, Bart Scheenstra, Joost Verbeek, Anke Bruninx, Petros Kalendralis, Inigo Bermejo, Andre Dekker, Arnoud van 't Hof, Marieke Spreeuwenberg, Laura Hochstenbach

“…Most of these features include goal setting, decision cards to help decide on an intervention, intervention monitoring, remote communication, and education, all accessible from one dashboard. A practice nurse or physician consults the individuals after risk calculation with the clinical prediction model and uses behavior change features, such as the decision cards, to support shared decision-making. …”
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