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

    Mohammed Yousef Shaheen (see profile)
    Artificial intelligence, Machine learning
    Item Type:
    #healthcare, Quality of Healthcare Services
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    The objective of this research was to investigate benefits and challenges of AI in healthcare. We divided the benefits into two subcategories: benefits related to the medical domain, and the benefits related to economic and social lives domain. The findings are: 1) Smart data inclusion contributes significantly and help to improve decision-making quality. 2) Surgical robots have improved the precision and predictability of the surgery. 3) Intraoperative guidance via video pictures and communication systems has proven to be beneficial, particularly in situations when there is a poor access to clinics, travel limitations, or pandemic. 4) Sentiment analysis analyzes, interprets, and responds to verbal expressions of human emotions. 6) Data scientists have been able to create algorithms that can comprehend human feeling from written text with unique combination of NLP and sentiment analysis. 7) AI could re-balance a clinician's workload, providing them more time to connect with patients and thereby improve care quality. The major challenges are: 1) the data reflects sometimes inherent biases and disparities in the healthcare system. 2) The demand for huge datasets incentivizes developers to acquire data from a large number of patients. Some patients may be worried that this data 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 will always be good; it has the potential to be detrimental. There are some improvements that benefit and there are some challenges that may harm, and these challenges must be responded by future research.
    Last Updated:
    1 year ago
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