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Abstract #3118

Applicable diagnostic model for detecting patients with mental disorders with magnetic resonance imaging

Wenjing Zhang1, Chengmin Yang1, Zehong Cao2, Feng Shi2, and Su Lui1
1Department of Radiology, West China Hospital of Sichuan University, Chengdu, China, 2Department of Research and Development, Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China


To yield clinical utility in mental disorder identification individually, we used a multiple instance learning-based method to construct a digital model based on clinical MRI scans for automated detection of patients with psychiatric disorders. An accuracy of 84% was achieved in the primary dataset with 19453 subjects, and 76% in external dataset with 600 subjects. A higher sensitivity was achieved in identifying high-risk subjects than self-scaled questionnaires (71.1% vs 22.2%) in 148 prospectively recruited college students. With a complete workflow of development and validation, the constructed model is more practical to be translated in high-risk subject screening among vulnerable populations.

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