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. 2024 May 22;5(4):100648. doi: 10.1016/j.xinn.2024.100648

Figure 1.

Figure 1

Overview of the multimodal integration (MMI) pipeline for pulmonary infection management

(A) Patients were identified and divided into training (WCH, N = 19,046), validation (WCH, N = 2,432), internal (WCH, N = 2,433), and external testing (CSJH; N = 196) datasets for the MMI system.

(B) Development of the MMI system through the integration of multimodal data. It integrated multimodal information, including unstructured text, images, lab assay results, and structured text to construct the system.

(C) Application of the MMI system in clinical settings for the diagnosis of infectious diseases, identification of pathogens, and risk prediction of critical patients, showcasing the actual utility of the AI model in managing pulmonary infections. CSJH, Chengdu ShangJin Nanfu Hospital; ICU, intensive care unit; WCH, West China Hospital.