Stroke is a leading cause of long-term disability, often affecting upper-limb motor function and requiring continuous assessment. The Fugl-Meyer Assessment (FMA), though a clinical gold standard, is time-consuming and demands specialized personnel. T... read more
Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
Jan 28, 2026
Global population aging and increased chronic stress due to numerous mass disasters including those related to pandemics, climate change, war, displacement, and political unrest all challenge our collective resilience, with a growing burden of late-l... read more
Journal of imaging informatics in medicine
Jan 28, 2026
This study presents a multi-stage deep learning pipeline for automated Angle's classification of occlusion using intraoral images in orthodontics. The pipeline integrates three key stages: (1) a binary Occlusion Side Classifier (OSC) to determine whe... read more
Computerized features derived from medical imaging have shown great potential in building machine learning models for predicting and prognosticating disease outcomes. However, the performance of such models depends on the robustness of extracted feat... read more
OBJECTIVES: To develop and validate a multi-task deep learning (MTDL) model using multiphase contrast-enhanced CT (CECT) for simultaneously assessing histological subtypes, clinical stages, and anatomical complexity grades of solid malignant renal tu... read more
OBJECTIVE: To evaluate the diagnostic performance of semi-supervised learning models for aggressive prostate cancer detection on MRI compared to fully supervised models trained with additional expert annotations. MATERIALS AND METHODS: We used 1500 M... read more
Journal of chemical information and modeling
Jan 28, 2026
The tumor suppressor p53 regulates transcription in response to cellular stress, with mutations in its DNA-binding domain (DBD) found in most human cancers. The L1 loop within the DBD is believed to play a critical role in DNA recognition, yet its co... read more
Understanding and predicting catalyst performance from structural and electronic information remains a central challenge in organocatalysis. Here, we present a data-integrated framework that quantitatively combines experimental, computational, and ma... read more
Journal of chemical information and modeling
Jan 28, 2026
Using machine learning to accelerate the characterization and prediction of properties of many-molecule systems, such as polymers, is appealing, yet challenging. Polymers are large, complex molecules that have unique properties and potential applicat... read more
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