BACKGROUND: Biomarker discovery exploiting feature importance of machine learning has risen recently in the microbiome landscape with its high predictive performance in several disease states. To have a concrete selection among a high number of featu...
Approaches to integrating mixed methods into medical research are gaining popularity. To get a holistic understanding of the effects of behavioural interventions, we investigated religious fasting using a triangulation of quantitative, qualitative, a...
European archives of psychiatry and clinical neuroscience
Oct 25, 2023
Blunted affect is associated with severe mental illness, particularly schizophrenia. Mechanisms of blunted affect are poorly understood, potentially due to a lack of phenomenological clarity. Here, we examine clinician rated blunted affect and comput...
International journal of surgical pathology
Oct 25, 2023
Ulcerative colitis (UC) is an intractable disease that affects young adults. Histological findings are essential for its diagnosis; however, the number of diagnostic pathologists is limited. Herein, we used a no-code artificial intelligence (AI) plat...
Journal of magnetic resonance imaging : JMRI
Oct 25, 2023
BACKGROUND: "Batch effect" in MR images, due to vendor-specific features, MR machine generations, and imaging parameters, challenges image quality and hinders deep learning (DL) model generalizability.
Training costs for operators of robotic arms in forestry and construction are high. A systematic analysis of skill development can help to make training more efficient. This research focuses on motor skill development by investigating the bimanual co...
Administration and policy in mental health
Oct 25, 2023
Mental health services are experiencing notable transformations as innovative technologies and artificial intelligence (AI) are increasingly utilized in a growing number of studies and services.These cutting-edge technologies carry the promise of sub...
Journal of hepato-biliary-pancreatic sciences
Oct 25, 2023
Tashiro and colleagues demonstrated for the first time that an artificial intelligence system can precisely identify intrahepatic vascular structures during laparoscopic liver resection in real time through color coding under bleeding and indocyanine...
Causal inference from observational data requires untestable identification assumptions. If these assumptions apply, machine learning methods can be used to study complex forms of causal effect heterogeneity. Recently, several machine learning method...
Biomedical knowledge graphs (BKGs) provide a new paradigm for managing abundant biomedical knowledge efficiently. Today's artificial intelligence techniques enable mining BKGs to discover new knowledge. Here, we present a protocol for implementing a ...
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