Research
Title : | Radiological AI system for Parallel Informatic Detection of Clinical Triage emergencies (RAPID-CT): Phase 2 |
Area of research : | Computer Sciences and Information Technology, Life Sciences & Biotechnology, Medical Sciences |
Focus area : | Generalisation of AI model |
Principal Investigator : | Debasis Dash, Scientist, CSIR-Institute of Genomics & Integrative Biology (CSIR-IGIB), New Delhi |
Timeline Start Year : | 2020 |
Timeline End Year : | 2022 |
Contact info : | director@igib.res.in |
Details
Executive Summary : | Objective: A. Development of an online or locally deployable AI system for detection of Intracranial Bleeds B. Validation of the developed AI model and system in a clinical setting C. Development of a methodology to enable generalization of the AI model for multiple hospitals D. Extending the developed methods onto other different conditions Summary: AI, despite having tremendous potential, has seen relatively low implementation in medical practice across India. Standard procedure for clinical triage emergencies such as CT or X-ray requires a radiologist which are either unavailable in remote areas or in high demand where available leading to delay in reports for possibly fatal conditions while posing significant stress on the radiologists. Recently in a previous project, we have successfully built and implemented deep learning (DL) models for early detection of intracranial bleeds having 95% accuracy. In this proposal, we intend to deploy and validate DL models in hospitals while extending our methods to triage of ureteric stones and gastrointestinal perforation. |