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In Journal of medical Internet research ; h5-index 88.0

BACKGROUND : Coronavirus Disease 2019 (COVID-19) was first discovered in December 2019 and has since evolved into a pandemic.

OBJECTIVE : To address this global health crisis, artificial intelligence (AI) has been deployed at various levels of the healthcare system. However, AI has both potential benefits and limitations. We therefore conducted a review of AI applications for COVID-19.

METHODS : We performed an extensive search of the PubMed and Embase databases for COVID-19-related English-language studies published between 1/12/2019 and 31/3/2020. We supplemented the database search with reference list checks. Thematic analysis and narrative review of AI applications for COVID-19 documented was conducted.

RESULTS : 11 papers were included for review. AI was applied to COVID-19 in four areas: diagnosis, public health, clinical decision-making, and therapeutics. We identified several limitations including insufficient data, omission of multimodal methods of AI-based assessment, delay in realization of benefits, poor internal/external validation, inability to be used by laypersons, inability to be used in resource-poor settings, presence of ethical pitfalls and presence of legal barriers. AI could potentially be explored in four other areas: surveillance, combination with big data, operation of other core clinical services, and management of COVID-19 patients.

CONCLUSIONS : In view of the continuing increase in infected cases, and given that multiple waves of infections may occur, there is need for effective methods to help control the COVID-19 pandemic. Despite its shortcomings, AI holds the potential to greatly augment existing human efforts, which may otherwise be overwhelmed by large patient numbers.

CLINICALTRIAL :

Chen Jiayang, See Kay Choong

2020-Sep-15