AI in Healthcare: medical and socio-economic benefits and challenges

Abstract

The objective of this research was to investigate benefits and challenges of AI in healthcare. Wedivided the benefits into two subcategories: benefits related to the medical domain, and the benefitsrelated to economic and social lives domain. The findings are: 1) Smart data inclusion contributessignificantly and help to improve decision-making quality. 2) Surgical robots have improved theprecision and predictability of the surgery. 3) Intraoperative guidance via video pictures andcommunication systems has proven to be beneficial, particularly in situations when there is a pooraccess to clinics, travel limitations, or pandemic. 4) Sentiment analysis analyzes, interprets, andresponds to verbal expressions of human emotions. 6)Data scientists have been able to create algorithmsthat can comprehend human feeling from written textwith unique combination of NLP and sentimentanalysis. 7) AI could re-balance a clinician's workload,providing them more time to connect with patientsand thereby improve care quality. The majorchallenges are: 1) the data reflects sometimesinherent biases and disparities in the healthcare system. 2) The demand for huge datasets incentivizesdevelopers to acquire data from a large number of patients. Some patients may be worried that thisdata collection would infringe on their confidentiality. 3) AI systems may occasionally be incorrect,resulting in patient damage or other health-care issues. It is not assumed that a new technology willalways be good; it has the potential to be detrimental. There are some improvements that benefit andthere are some challenges that may harm, and these challenges must be responded by futureresearch.

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