Previous resting state functional MRI (rs-fMRI) analyses of the basal ganglia in Parkinson's disease heavily relied on T1-weighted imaging (T1WI) atlases. However, subcortical structures are characterized by subtle contrast differences, making their ...
BACKGROUND: The Aberrant Salience (AS) model conceptualizes psychosis onset as the altered attribution of salience to neutral stimuli. The Aberrant Salience Inventory (ASI), a psychometric tool, measures this phenomenon. This study utilized a multi-c...
Clinical data warehouses, which have arisen over the last decade, bring together the medical data of millions of patients and offer the potential to train and validate machine learning models in real-world scenarios. The quality of MRIs collected in ...
BACKGROUND: Monitoring intrinsic capacity and implementing appropriate interventions can support healthy aging. There are, though, few tools available for predicting decline in intrinsic capacity among older adults. This study aimed to develop and va...
The application of machine learning methods to the groundwater pollution inversion problem has become a hot research topic in recent years. However, applying machine learning methods to achieve synergistic and rapid identification of pollution source...
OBJECTIVE: We aimed to develop a machine learning (ML) model to preoperatively predict surgical difficulty for pheochromocytomas and paragangliomas (PPGLs) using clinical and radiomic features.
To explore the capabilities of race/ethnicity and gender prediction algorithms in uncovering patterns of authorship distribution in scientific paper submissions to a major peer-reviewed scientific journal (), we analyzed 17 667 manuscript submissions...
International journal of pediatric otorhinolaryngology
Jul 1, 2025
BACKGROUND: Artificial Intelligence (AI) and machine learning (ML) have transformative potential in enhancing diagnostics, treatment planning, and patient management. However, their application in pediatric otolaryngology remains limited as the uniqu...
Computer methods and programs in biomedicine
Jul 1, 2025
OBJECTIVES: Achieving efficient analysis of multiple pathological indicators has great significance for breast cancer prognosis and therapeutic decision-making. In this study, we aim to explore a deep multi-task learning (MTL) framework for collabora...
Machine learning has the potential to support the growing need for high-resolution greenhouse gas monitoring in urban and industrial environments, where deploying extensive sensor networks is often limited by cost and operational challenges. This stu...
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