2019
DOI: 10.1177/1062860619878515
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Application of Artificial Intelligence in the Health Care Safety Context: Opportunities and Challenges

Abstract: There is a growing awareness that artificial intelligence (AI) has been used in the analysis of complicated and big data to provide outputs without human input in various health care contexts, such as bioinformatics, genomics, and image analysis. Although this technology can provide opportunities in diagnosis and treatment processes, there still may be challenges and pitfalls related to various safety concerns. To shed light on such opportunities and challenges, this article reviews AI in health care along wit… Show more

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Cited by 100 publications
(69 citation statements)
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“…dynamic scheduling systems with the use of predictive analytics tools via machine learning and artificial intelligence, may help healthcare organizations to reduce and absorb the impact of no-shows. Aiming to make healthcare more effective and efficient, 24 such approaches would enable better match supply with expected demand under such circumstances. The recommendations below for the scheduling process may also be helpful for the purpose of reducing no-show rates:…”
Section: Discussionmentioning
confidence: 99%
“…dynamic scheduling systems with the use of predictive analytics tools via machine learning and artificial intelligence, may help healthcare organizations to reduce and absorb the impact of no-shows. Aiming to make healthcare more effective and efficient, 24 such approaches would enable better match supply with expected demand under such circumstances. The recommendations below for the scheduling process may also be helpful for the purpose of reducing no-show rates:…”
Section: Discussionmentioning
confidence: 99%
“…While discussion on this may be lengthy, following issues like proprietary pursuit by some device manufacturers, and the forfeiture of profits by the corporations that may benefit from the handling of such data, the potential that the processing of the data from unrestricted dataset is limitless [40]. This, as Ellahham et al [44] hold, would greatly benefit the health sector in scaling issues like diagnosis, personalised medication and the discovery of cures for ailments that bedevils the global population.…”
Section: On Ai-driven Algorithms and Bioinformaticsmentioning
confidence: 99%
“…The promising counter-resistance plan has attempted to convince the embryologists, slowly and patiently, by introducing simple and practical training. Unfortunately, adapting ML into healthcare systems is not simple [98]. Changing well-structured healthcare systems is difficult.…”
Section: Discussionmentioning
confidence: 99%