Recognition and management of auditory verbal hallucinations in borderline personality disorder by M. B. A. Niemantsverdriet, M. B. A. Niemantsverdriet, C. W. Slotema, C. W. Slotema, I. H. A. Franken, J. Brandsma, M. J. P. M. Verbraak, M. L. Deen, J. D. Blom, J. D. Blom, J. D. Blom, M. Van der Gaag

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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

“…Integrating health, social care and education data, we developed several machine learning models aimed at predicting childhood mental health problems. …”
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An Optimal Internet of Things-Driven Intelligent Decision-Making System for Real-Time Fishpond Water Quality Monitoring and Species Survival by Saima Kanwal, Muhammad Abdullah, Sahil Kumar, Saqib Arshad, Muhammad Shahroz, Dawei Zhang, Dileep Kumar

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Multimorbidity of cardiometabolic diseases: a cross-sectional study of patterns, clusters and associated risk factors in sub-Saharan Africa by Charles Agyemang, Frederick Wekesah, Calistus Wilunda, Gershim Asiki, Peter Otieno, Richard E Sanya, Welcome Wami

“…Objective To determine the patterns of cardiometabolic multimorbidity and associated risk factors in sub-Saharan Africa (SSA).Design We used data from the WHO STEPwise approach to non-communicable disease risk factor surveillance cross-sectional surveys conducted between 2014 and 2017.Participants The participants comprised 39, 658 respondents aged 15–69 years randomly selected from nine SSA countries using a multistage stratified sampling design.Primary outcome measure Using latent class analysis and agglomerative hierarchical clustering algorithms, we analysed the clustering of cardiometabolic diseases (CMDs) including high blood sugar, hypercholesterolaemia, hypertension and cardiovascular diseases (CVDs) such as heart attack, angina and stroke. …”
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Artificial intelligence in molecular and genomic prostate cancer diagnostics by A. O. Morozov, A. K. Bazarkin, S. V. Vovdenko, M. S. Taratkin, M. S. Balashova, D. V. Enikeev

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Bibliometric analysis and review of AI-based video generation: research dynamics and application trends (2020–2025) by Wei Xie, Anshu Hu, Qing Xie, Junjie Chen, Ruoyu Wan, Yuhan Liu

“…Our findings the rise of specific architectures, pinpoint high-activity application areas, reveal evolving thematic clusters, and also remarks persistent challenges, including technical hurdles and critical ethical issues such as deepfake detection, algorithmic transparency, and data privacy. By synthesizing these analyses, this study offers a structured overview of the recent landscape, and highlights areas that may warrant further exploration in AI video generation.…”
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Committee Machine Learning for Electrofacies-Guided Well Placement and Oil Recovery Optimization by Adewale Amosu, Dung Bui, Oluwapelumi Oke, Abdul-Muaizz Koray, Emmanuel Appiah Kubi, Najmudeen Sibaweihi, William Ampomah

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Predicting mortality risk in Alzheimer’s disease using machine learning based on lifestyle and physical activity by Ruihong Tang, Liang Tan, Xia Chen, Zhengwu Shan, Zhao Zhang, Panpan Cheng

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Enhancing Triage Systems in Emergency Units: An Extensive Review by Dipankar Maiti, Tincy Mariam Easow, Jyothi R

“…Technological advancements such as the integration of Electronic health records EHRs and real-time data analytics offer promising avenues for improvement. …”
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History of Location Objectives (Hilal Tracker): Development of Astronomical Observations from 2015-Present by Marataon Ritonga, Alya Fathi Muhammad Hasibuan, Rizqan Arya Perdana Nazara

“…This article explains the history of the development of hilal Tracker technology and methods, including integrating astronomical data, using satellite imagery, algorithms for predicting hilal visibility, and cooperation with various local and international institutions. …”
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Application of Machine Learning for Real-Time Phishing Attack Detection by Akshay Shankar Agrawal, Sanketi Raut, Andrina Dsouza, Jimit Mehta, Prajwal Naik

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STBNA-YOLOv5: An Improved YOLOv5 Network for Weed Detection in Rapeseed Field by Tao Tao, Xinhua Wei

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Continuous Glucose Monitoring: A Transformative Approach to the Detection of Prediabetes by Liu X, Zhang J

“…CGM technology provides real-time, continuous data on glucose concentrations, surpassing the constraints of conventional monitoring methods. …”
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Personalised Prostate Cancer Diagnosis: Evaluating Biomarker-based Approaches to Reduce Unnecessary Magnetic Resonance Imaging and Biopsy Procedures by Timo F.W. Soeterik, Xiaobo Wu, Roderick C.N. Van den Bergh, Claudia Kesch, Fabio Zattoni, Ugo Falagario, Alberto Martini, Marcin Miszczyk, Vittorio Fasulo, Martina Maggi, Veeru Kasivisvanathan, Pawel Rajwa, Giancarlo Marra, Giorgio Gandaglia, Peter K.F. Chiu

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Geographical variation of overweight, obesity and related risk factors: Findings from the European Health Examination Survey in Luxembourg, 2013-2015. by Hanen Samouda, Maria Ruiz-Castell, Valery Bocquet, Andrea Kuemmerle, Anna Chioti, Frédéric Dadoun, Ngianga-Bakwin Kandala, Saverio Stranges

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Academic response to improving value and reducing waste: A comprehensive framework for INcreasing QUality In patient-oriented academic clinical REsearch (INQUIRE). by Belinda von Niederhäusern, Gordon H Guyatt, Matthias Briel, Christiane Pauli-Magnus

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Construction of disability risk prediction model for the elderly based on machine learning by Jing Chen, Yifei Ren, Jie Ding, Qingqing Hu, Jiajia Xu, Jun Luo, Zhaowen Wu, Ting Chu

“…Abstract The study aimed to develop a predictive model using machine learning algorithms, providing healthcare professionals with a novel tool for assessing disability risk in older adults. …”
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AirQuaNet: A Convolutional Neural Network Model With Multi-Scale Feature Learning and Attention Mechanisms for Air Quality-Based Health Impact Prediction by Sreeni Chadalavada, Suleyman Yaman, Abdulkadir Sengur, Ravinesh C. Deo, Abdul Hafeez-Baig, Tracy Kolbe-Alexander, Niranjana Sampathila, U. Rajendra Acharya

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A learning trajectory for developing computational thinking in prospective mathematics teachers through Python programming in Google Colab by Edi Irawan, Moh. Khoridatul Huda, Ratni Purwasih

“…The results showed that HLT, designed in stages, improved the four main components of CT: decomposition, abstraction, pattern recognition, and algorithmic thinking. The students experienced improvements in breaking down problems, devising more efficient solutions, recognising patterns in code structures, and systematically designing algorithms. …”
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An online 11 kv distribution system insulator defect detection approach with modified YOLOv11 and mobileNetV3 by Arnav Bhagwat, Soham Dutta, Debdeep Saha, Maddikara Jaya Bharata Reddy

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