Multimodal system enhances diagnostic accuracy for hepatic conditions

A deep learning diagnostic system combining CT and ultrasound achieved superior accuracy in detecting hepatic echinococcosis and other liver conditions compared to individual modalities and physician evaluations. The integrated model demonstrated an impressive accuracy of 81.6% in internal tests and 84.9% in external assessments, with high sensitivity and specificity. This innovation significantly reduces misdiagnosis rates, showcasing the potential of multimodal imaging in improving diagnostic reliability in underserved healthcare settings.