Clinical Research Directory

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.

Saudi Emergency Laparotomy Audit

The Saudi Emergency Laparotomy Audit (SELA) is a national, multicenter observational clinical audit designed to evaluate outcomes and quality of care for patients undergoing emergency laparotomy in Saudi Arabia. The audit will collect standardized data on patient characteristics, comorbidities, perioperative processes, and postoperative outcomes through a retrospective baseline phase followed by a prospective registry phase. SELA aims to establish national benchmarks, assess applicability of international risk models, support development of a Saudi-specific risk prediction tool, and drive quality improvement through systematic feedback and benchmarking across participating hospitals.