Promise and Provisos of Artificial Intelligence and Machine Learning in Healthcare

被引:8
|
作者
Bhardwaj, Anish [1 ,2 ,3 ,4 ,5 ,6 ,7 ,8 ]
机构
[1] Univ Texas Med Branch UTMB, Dept Neurol, Galveston, TX USA
[2] Univ Texas Med Branch UTMB, Dept Neurosurg, Galveston, TX USA
[3] Univ Texas Med Branch UTMB, Dept Neurosci, Galveston, TX USA
[4] Univ Texas Med Branch UTMB, Dept Cell Biol & Anat, Galveston, TX USA
[5] Univ Texas Med Branch UTMB, Dept Neurol, 9 128 John Sealy Annex,Route 0539,01 Univ Blvd, Galveston, TX 77555 USA
[6] Univ Texas Med Branch UTMB, Dept Neurosurg, 9 128 John Sealy Annex,Route 0539,01 Univ Blvd, Galveston, TX 77555 USA
[7] Univ Texas Med Branch UTMB, Dept Neurosci, 9 128 John Sealy Annex,Route 0539,01 Univ Blvd, Galveston, TX 77555 USA
[8] Univ Texas Med Branch UTMB, Dept Cell Biol & Anat, 9 128 John Sealy Annex,Route 0539,01 Univ Blvd, Galveston, TX 77555 USA
来源
关键词
artificial intelligence; machine learning; cost; -benefit; healthcare;
D O I
10.2147/JHL.S369498
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Artificial Intelligence (AI) and Machine Learning (ML) promise to transform all facets of medicine. Expected changes include more effective clinical triage, enhanced accuracy of diagnostic interpretations, improved therapeutic interventions, augmented workflow algorithms, streamlined data collection and processing, more precise disease prognostication, newer pharmacotherapies, and ameliorated genome interpretation. However, many caveats remain. Reliability of input data, interpretation of output data, data proprietorship, consumer privacy, and liability issues due to potential for data breaches will all have to be addressed. Of equal concern will be decreased human interaction in clinical care, patient satisfaction, affordability, and skepticism regarding cost-benefit. This descriptive literature-based treatise expounds on the promise and provisos associated with the anticipated import of AI and ML into all domains of medicine and healthcare in the very near future.
引用
收藏
页码:113 / 118
页数:6
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