Sabharwal Renu, Miah Shah J, Fosso Wamba Samuel
Newcastle Business School, The University of Newcastle, Callaghan, NSW Australia.
TBS Business School, Toulouse, France.
Ann Oper Res. 2022 Nov 8:1-32. doi: 10.1007/s10479-022-05035-1.
Academic research to the utilization of artificial intelligence (AI) has been proliferated over the past few years. While AI and its subsets are continuously evolving in the fields of marketing, social media and finance, its application in the daily practice of clinical care is insufficiently explored. In this systematic review, we aim to landscape various application areas of clinical care in terms of the utilization of machine learning to improve patient care. Through designing a specific smart literature review approach, we give a new insight into existing literature identified with AI technologies in the clinical domain. Our review approach focuses on strategies, algorithms, applications, results, qualities, and implications using the Latent Dirichlet Allocation topic modeling. A total of 305 unique articles were reviewed, with 115 articles selected using Latent Dirichlet Allocation topic modeling, meeting our inclusion criteria. The primary result of this approach incorporates a proposition for future research direction, abilities, and influence of AI technologies and displays the areas of disease management in clinics. This research concludes with disease administrative ramifications, limitations, and directions for future research.
在过去几年里，关于人工智能（AI）应用的学术研究大量涌现。虽然AI及其分支在市场营销、社交媒体和金融领域不断发展，但其在临床护理日常实践中的应用仍未得到充分探索。在本系统综述中，我们旨在探讨机器学习在临床护理中的各种应用领域，以改善患者护理。通过设计一种特定的智能文献综述方法，我们对临床领域中已识别的使用AI技术的现有文献有了新的见解。我们的综述方法使用潜在狄利克雷分配主题模型，重点关注策略、算法、应用、结果、质量和影响。总共审查了305篇独特的文章，其中115篇文章通过潜在狄利克雷分配主题模型筛选出来，符合我们的纳入标准。这种方法的主要结果包括对AI技术未来研究方向、能力和影响的建议，并展示了临床疾病管理领域。本研究最后得出疾病管理的影响、局限性以及未来研究方向。
