Bhardwaj Anish
Departments of Neurology, Neurosurgery, Neuroscience, Cell Biology and Anatomy, University of Texas Medical Branch (UTMB), Galveston, TX, USA.
J Healthc Leadersh. 2022 Jul 20;14:113-118. doi: 10.2147/JHL.S369498. eCollection 2022.
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.
人工智能（AI）和机器学习（ML）有望变革医学的各个方面。预期的变化包括更有效的临床分诊、提高诊断解读的准确性、改进治疗干预措施、增强工作流程算法、简化数据收集和处理、更精确的疾病预后、更新的药物治疗方法以及改善基因组解读。然而，仍有许多需要注意的地方。输入数据的可靠性、输出数据的解读、数据所有权、消费者隐私以及因数据泄露可能性而产生的责任问题都必须得到解决。同样令人担忧的将是临床护理中人际互动的减少、患者满意度、可负担性以及对成本效益的怀疑态度。这篇基于文献的描述性论文阐述了在不久的将来人工智能和机器学习有望引入医学和医疗保健所有领域的前景及附带条件。
