NCT07040358

Rapid Abdominal Diagnosis With AI & Radiology

Development and Application of an AI Model for Accurate Interpretation of Abdominal Enhanced CT Images

• Status: Active Not Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 2,000,000 (estimated)
• Sponsor: First Affiliated Hospital of Zhejiang University · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Accepted

Summary

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.

Conditions

• Abdominal Diseases

Timeline

• Start date: 2023-12-01
• Primary completion: 2025-09-30
• Completion: 2026-06-01
• First posted: 2025-06-27
• Last updated: 2026-03-05

Locations

1 site across 1 country: China