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Nosa Aikodon, Sandra Ortega-Martorell and Ivan Olier
Patients in Intensive Care Units (ICU) face the threat of decompensation, a rapid decline in health associated with a high risk of death. This study focuses on creating and evaluating machine learning (ML) models to predict decompensation risk in ICU pat...
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Aquib Raza, Thien-Luan Phan, Hung-Chung Li, Nguyen Van Hieu, Tran Trung Nghia and Congo Tak Shing Ching
Knee osteoarthritis (KOA) is a leading cause of disability, particularly affecting older adults due to the deterioration of articular cartilage within the knee joint. This condition is characterized by pain, stiffness, and impaired movement, posing a sig...
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Paraskevi Detopoulou, Panos Papandreou, Lida Papadopoulou and Maria Skouroliakou
Clinical Decision Support Systems (CDSSs) facilitate evidence-based clinical decision making for health professionals. Few studies have applied such systems enabling distance monitoring in the COVID-19 epidemic, especially in a hospital setting. The purp...
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Thomas T. H. Wan and Hunter S. Wan
Context. This commentary is based on an innovative approach to the development of predictive analytics. It is centered on the development of predictive models for varying stages of chronic disease through integrating all types of datasets, adds various n...
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Zimei Zhang, Jianwei Xiao, Shanyu Wang, Min Wu, Wenjie Wang, Ziliang Liu and Zhian Zheng
The accurate identification of the origin of Chinese medicinal materials is crucial for the orderly management of the market and clinical drug usage. In this study, a deep learning-based algorithm combined with machine vision was developed to automatical...
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Mohamed Hassan Elnaem, Merna Mahmoud AbouKhatwa, Mahmoud E. Elrggal and Inderpal Singh Dehele
Globally, the prevalence of attention deficit hyperactivity disorder (ADHD) is increasing. The treatment for ADHD is multifaceted and requires long-term care and support. Pharmacists are capable of assisting patients and their caretakers in achieving des...
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Jie Xu, Xing He, Wei Shao, Jiang Bian and Russell Terry
Up to 20% of renal masses =4 cm is found to be benign at the time of surgical excision, raising concern for overtreatment. However, the risk of malignancy is currently unable to be accurately predicted prior to surgery using imaging alone. The objective ...
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Muhammad Shoaib Arif, Aiman Mukheimer and Daniyal Asif
Clinical decision-making in chronic disorder prognosis is often hampered by high variance, leading to uncertainty and negative outcomes, especially in cases such as chronic kidney disease (CKD). Machine learning (ML) techniques have emerged as valuable t...
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Nisrine Berros, Fatna El Mendili, Youness Filaly and Younes El Bouzekri El Idrissi
Medicine is constantly generating new imaging data, including data from basic research, clinical research, and epidemiology, from health administration and insurance organizations, public health services, and non-conventional data sources such as social ...
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Ruhi Kiran Bajaj, Rebecca Mary Meiring and Fernando Beltran
Computational analysis and integration of smartwatch data with Electronic Medical Records (EMR) present potential uses in preventing, diagnosing, and managing chronic diseases. One of the key requirements for the successful clinical application of smartw...
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