The rapid expansion of the electric vehicle industry has resulted in substantial production of NdFeB magnet wastes from discarded electromotors. These magnets, weighing up to 2 kg in each electromotor, contain 25-35 wt% of strategic rare earth elemen...
BACKGROUND: Anastomotic strictures (AS) frequently occurs in patients following esophageal cancer surgery, significantly affecting their long-term quality of life. This study aims to develop a machine learning model to predict high-risk AS, enabling ...
BACKGROUND: Traditional risk models, such as POSSUM and OS-MS, have limited accuracy in predicting complications after bariatric surgery. Machine learning (ML) offers new opportunities for personalized risk assessment by incorporating artificial inte...
Application of machine learning-based methods to identify novel bacterial enzymes capable of degrading a wide range of xenobiotics offers enormous potential for bioremediation of toxic and carcinogenic recalcitrant xenobiotics such as pesticides, pla...
Lung adenocarcinoma (LUAD) is a morphologically heterogeneous disease, characterized by five primary histological growth patterns. The classification of such patterns is crucial due to their direct relation to prognosis but the high subjectivity and ...
BACKGROUND: Many machine learning (ML) algorithms have been used to develop surgical site infection (SSI) prediction models, but little is known about their predicting performance. We conducted a network meta-analysis to compare the performance of di...
Adverse Drug Reactions (ADRs) during pregnancy pose significant risks to both the mother and the fetus. Conventional approaches to predict ADR are inadequate due to ethical restrictions that prevent performing medication studies in pregnant women, le...
BACKGROUND: Segmentation is a critical process in medical image interpretation. It is also essential for preparing training datasets for machine learning (ML)-based solutions. Despite technological advancements, achieving fully automatic segmentation...
INTRODUCTION: High-throughput fluorescence imaging (HTFI) is revolutionizing drug discovery by enabling rapid and precise detection of biological targets and cellular processes. Recent advances in fluorescence imaging technologies now provide unprece...
International journal of sports physiology and performance
Jun 1, 2025
PURPOSE: Accurately predicting the distance covered by athletes during indoor sport activities without the use of GPS (global positioning systems) presents a significant challenge. This study evaluates the effectiveness of various machine-learning te...
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