Rapid Abdominal Diagnosis With AI & Radiology

This study aims to develop an AI-assisted diagnostic system for abdominal contrast-enhanced CT images using data from multiple inpatient centers. In collaboration with Alibaba DAMO Academy, the project will address key mathematical challenges limiting current automated image interpretation, including feature space alignment, hybrid reasoning, and multimodal report generation. The study includes the following components: (1) construction of a dual-modality foundation model to align abdominal CT features with corresponding radiology reports; (2) development of a model to standardize CT phase variation among patients; and (3) creation of an automated image interpretation and reporting system that integrates multi-source clinical data. The effectiveness of the system will be evaluated through a report quality assessment framework and clinical validation. This project aims to improve the accuracy and clinical applicability of automated abdominal disease interpretation and promote intelligent innovation in healthcare delivery.

NCT Number	NCT07040358
Lead Sponsor	First Affiliated Hospital of Zhejiang University Collaborators: the First Division Hospital of Xinjiang Production and Construction Corps, The First People's Hospital of Yuhang District, Affiliated Hospital of Jiaxing University, Jixi County People's Hospital, Anji County People's Hospital, Zhejiang University, People's Hospital of Beilun District, Ningbo City, Haining People's Hospital, People's Hospital of Jingning She Autonomous County
Conditions	Abdominal Diseases
Enrollment	2,000,000 participants
Start Date	2023-12-01
Primary Completion	2025-09-30 (estimated)
Study Completion	2026-06 (estimated)
Updated on ClinicalTrials.gov	2026-03-05