Dr Clarice Choong Shi Hui | National University Hospital (NUH); Francis Ho Cho Hao, Co-I | NUH, Melissa Ooi Gaik Ming. Co-I | NUH; Leo Hwa Liang, Co-I | NUS; Matthew Chen Zhixuan, Co-I | NUH; Nesaretnam Barr Kumarakulasinghe, Co-I | NUH; Pang Shien Ling Angela, Co-I | NUH; Jia Li Low, Co-I | NUH; Ling Mun Wai Natalie, Co-I | NUH ; Liu Zhanhong, Collab |NUS; Ng Yean Shin, Collab | NUHS
Competition Sponsor: Ministry of Health and National Research Foundation of Singapore
Awardee year: 2022
Our ageing population will be the key demographic change that will impact our country for the next 50 years and there will be a concurrent increase in the number of older adults being diagnosed with cancer. We already have in place a geriatric oncology service with provision of care for older cancer patients. These patients will undergo comprehensive geriatric assessment (CGA) which can identify impairments and gaps that may contribute to vulnerability and adverse outcomes. The ability to identify patients that are fit, pre-frail or frail is of paramount importance as we do not want to short-change our older cancer patients. The correct identification of this group of vulnerable patients will enable the oncologist to use a non-intensive regiment and avoid excessive toxicity whilst the patient can still enjoy a stable quality of life (QoL). We aim to develop an artificial intelligence (AI) model based on machine learning (ML) algorithms to assess the medical fitness of geriatric oncology patients as a replacement to the traditional CGA. This AI model will be designed to perform at least, as well as current CGA tool but utilising significantly less resources in terms of manpower and time.