The team will develop an AI system called JARVISDHL to gather local healthcare data in order to create AI algorithms and models. This will facilitate practice of evidence-based personalised care and shared-decision making by primary care physicians.
The project aims to integrate multiple solutions into a consolidated AI platform which can be used to improve the 3H care delivery process.
Click here to read about the team’s progress.
Principal Investigators & Collaborators
Lead Principal Investigator: Prof Wynne Hsu (NUS)
Co-Principal Investigators:
Professor Ng See-Kiong (NUS)
Professor Lee Mong Li (NUS)
Associate Professor Chee Yong Chan (NUS)
Professor Wong Tien-Yin (SingHealth)
Professor Marcus Ong Eng Hock (SingHealth)
Associate Professor Tan Ngiap Chuan (SingHealth)
Dr Teh Ming Ming (SingHealth)
Adjunct Associate Professor Yeo Khung Keong (SingHealth)
Host Institutions: National University of Singapore (NUS)
Partner Institution(s): SingHealth Group (SingHealth)
Benefits to Primary Care Team
Enable predictive care for 3H patients through early screening and risk stratification.
Facilitate practice of evidence-based personalised care and shared-decision making by primary care physicians.
Physicians will get to the right site-care of patients rather than the usual reactive event-driven sequential referral model, thus spending less physical time in healthcare institutions, optimizing healthcare utilization. For example, JARVIS will recommend evidence based treatment options, quantify personalised treatment benefits and risk of complications, adapt treatment regimen based on lifestyle, alleviate anxiety over perceived side effects and support holistic clinical decision-making
Benefits to End-users
Patients are empowered to take ownership of their healthcare journey beyond the clinical visits through the use of technologies for patient education and self care.
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