Enhancing Multidisciplinary Team Meetings via AI-Enabled Data Assimilation. Multidisciplinary team meetings (MDTs) involve multiple members discussing their relevant data for collaborative decision-ma

Description

Enhancing Multidisciplinary Team Meetings via AI-Enabled Data Assimilation. Multidisciplinary team meetings (MDTs) involve multiple members discussing their relevant data for collaborative decision-making. MDTs improve outcomes, but they are time and resource intensive with complex data preparation, integration, presentation and then summarisation. The project aims to innovate in artificial intelligence algorithms to automatically prepare, integrate, visualise, and summarise MDT data. A Hospital is an excellent microcosm for MDTs where image data are usually the centrepiece for discussion. This project expects to produce a software framework to enhance collaborative decision-making and efficiency. This should benefit healthcare industry and have wide applicability for MDTs across other industries.. Scheme: Mid-Career Industry Fellowships. Field: 4603 - Computer Vision and Multimedia Computation. Lead: Prof Jinman Kim