An end-to-end Adaptive AI-Assisted 3H Care (A3C) system

The proposal covers both the assessment and intervention for 3H patients. The system periodically assesses the status of 3H patients, as well as identifies pre-3H persons based on early behavioural patterns, health symptoms and other non-medical factors. The system will also provide individual and group-based adaptive, long-term interventions through gamification.

Click here to read about the team’s progress. 

Principal Investigators & Collaborators

Lead Principal Investigator: Professor Chunyan Miao (NTU)

Co-Principal Investigators: 

Associate Professor Chin Jing Jih (NHG/NTU)

Associate Professor Chng Eng Siong (NTU)

Assistant Professor Yu Han (NTU)

Dr Kirk Wong Chuan (NHG)

Associate Professor Steven Hoi (SMU)

Host Institutions: Nanyang Technological University (NTU)


Partner Institution(s): National Healthcare Group (NHG), Singapore Management University (SMU)

Benefits to Primary Care Team

  • Periodical Reports of Patients
  • Signal Pre-chronic Diseases
  • Early Medical Interventions

Apart from periodically reporting the status of patients with chronic diseases, the AI-assisted 3H Care (A3C) system will enable medical professionals to be alerted to early signs of pre-chronic diseases based on behavioural patterns, health symptoms and other non-medical factors.

Through continuous monitoring and assessment provided by the system, medical professionals are empowered to start early medical interventions to effectively slow down the progression of the chronic diseases and reduce associated complications.

Benefits to End-users

A3C is able to provide personalised recommendations based on the in-situ information collected from individual users, their surrounding environment as well as available medical guidelines and best practices.

An intuitive interface enables end users to interact easily with the system. A3C gamifies the daily or weekly intervention activities and incorporates peer support and competition mechanisms to improve user compliance with the interventions.

  • Received “Innovative Applications of AI” Award by the Association for the Advancement of Artificial Intelligence (IAAI 2020) 
  • 4 conference publications in international conferences [Empirical Methods in Natural Language Processing (EMNLP 2019), Autonomous Agents and Multi-Agent Systems (AAMAS 2020), Association for the Advancement of Artificial Intelligence (AAAI 2020), Innovative Applications of Artificial Intelligence (IAAI 2020)]
  • 4 journal publications in IEEE Internet of Things Journal, IEEE Communications Surveys and Tutorials, Neurocomputing and Neural Computing and Applications respectively