Background The development of artificial intelligence in surgery is limited by the scarcity of annotated datasets. Recent advances in medical image segmentation, such as the Medical Segment Anything Model (MedSAM), may facilitate efficient annotation of surgical videos by residents. Methods Eight surgical residents a...
Antonio S. Soares, L. Castro, Patricia Martins et al.· Scientific Reports· 0 citations
Multi-modal learning has demonstrated strong potential in medical applications by integrating heterogeneous data sources such as medical imaging, clinical records, and genomics to improve predictive performance and support clinical decision-making. However, advances in this area are often constrained by two key challen...
Rita Cordeiro Mendes, Maria Rita Verdelho, Carlos Santiago et al.· 0 citations
A two-stage framework separating symptom-candidate generation from definition-grounded verification of depression symptoms is proposed, which support decomposing symptom recognition into candidate generation and definition-grounded verification, though performance remains limited for rare categories.
Wei-Ming Li, Catarina Barata, M. Constante et al.· 0 citations
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