BACKGROUND: Machine learning (ML) and big data analytics are rapidly transforming health care, particularly disease prediction, management, and personalized care. With the increasing availability of real-world data (RWD) from diverse sources, such as...
BACKGROUND: Colorectal cancer is now the leading cause of cancer-related deaths among young Americans. Accurate early prediction and a thorough understanding of the risk factors for early-onset colorectal cancer (EOCRC) are vital for effective preven...
BACKGROUND: The opioid crisis poses a significant health challenge in the United States, with increasing overdoses and death rates due to opioids mixed with other illicit substances. Various strategies have been developed by federal and local governm...
OBJECTIVE: Endometriosis is a prevalent gynecological disease characterized by the ectopic growth of functional endometrial tissue outside the uterine cavity, affecting millions of women worldwide. Currently, the definitive diagnosis relies on invasi...
BACKGROUND: Cognitive behavioral therapy (CBT) is a first-line treatment for obsessive-compulsive disorder (OCD), but clinical response is difficult to predict. In this study, we aimed to develop predictive models using clinical and neuroimaging data...
BACKGROUND: Major depressive disorder (MDD) exhibits a multifactorial etiopathogenesis, yet current diagnosis still relies on clinician-rated symptom scales and phenomenological interviews, lacking validated biomarkers.
The co-contamination of multiple pollutants in complex environmental matrices poses a significant threat to ecosystems and public health, necessitating advanced detection methods. In this study, we developed a machine learning-powered chemical sensor...
Computer methods and programs in biomedicine
Jun 18, 2025
BACKGROUNDS AND OBJECTIVES: Cardiac arrhythmias, characterized by irregular heartbeats, are difficult to diagnose in real-world scenarios. Machine learning has advanced arrhythmia detection; however, the optimal number of heartbeats for precise class...
The simultaneous monitoring of both blood glucose level (BGL) and blood pressure (BP) has rarely been studied directly. The exploitation of physiological interactions between them will advance the learning of either task. However, the lack of availab...
Few-shot learning alleviates the heavy dependence of medical image segmentation on large-scale labeled data, but it shows strong performance gaps when dealing with new tasks compared with traditional deep learning. Existing methods mainly learn the c...
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