Application of Artificial intelligence in COVID-19-related geriatric care: A scoping review.

Background: Older adults have been disproportionately affected by the COVID-19 pandemic. This scoping review aimed to summarize the current evidence of artificial intelligence (AI) use in the screening/monitoring, diagnosis, and/or treatment of COVID-19 among older adults.

Method: The review followed the Joanna Briggs Institute and Arksey and O'Malley frameworks. An information specialist performed a comprehensive search from the date of inception until May 2021, in six bibliographic databases. The selected studies considered all populations, and all AI interventions that had been used in COVID-19-related geriatric care. We focused on patient, healthcare provider, and healthcare system-related outcomes. The studies were restricted to peer-reviewed English publications. Two authors independently screened the titles and abstracts of the identified records, read the selected full texts, and extracted data from the included studies using a validated data extraction form. Disagreements were resolved by consensus, and if this was not possible, the opinion of a third reviewer was sought.

Results: Six databases were searched , yielding 3,228 articles, of which 10 were included. The majority of articles used a single AI model to assess the association between patients' comorbidities and COVID-19 outcomes. Articles were mainly conducted in high-income countries, with limited representation of females in study participants, and insufficient reporting of participants' race and ethnicity.

Discussion: This review highlighted how the COVID-19 pandemic has accelerated the application of AI to protect older populations, with most interventions in the pilot testing stage. Further work is required to measure effectiveness of these technologies in a larger scale, use more representative datasets for training of AI models, and expand AI applications to low-income countries.