Wani Shahid Ud Din, Khan Nisar Ahmad, Thakur Gaurav, Gautam Surya Prakash, Ali Mohammad, Alam Prawez, Alshehri Sultan, Ghoneim Mohammed M, Shakeel Faiyaz
Department of Pharmaceutical Sciences, University of Kashmir, Jammu and Kashmir, Srinagar 190006, India.
Department of Pharmaceutics, CT Institute of Pharmaceutical Sciences, CT Group of Institutions, Jalandhar 144020, India.
Healthcare (Basel). 2022 Mar 24;10(4):608. doi: 10.3390/healthcare10040608.
Artificial intelligence (AI) has been described as one of the extremely effective and promising scientific tools available to mankind. AI and its associated innovations are becoming more popular in industry and culture, and they are starting to show up in healthcare. Numerous facets of healthcare, as well as regulatory procedures within providers, payers, and pharmaceutical companies, may be transformed by these innovations. As a result, the purpose of this review is to identify the potential machine learning applications in the field of infectious diseases and the general healthcare system. The literature on this topic was extracted from various databases, such as Google, Google Scholar, Pubmed, Scopus, and Web of Science. The articles having important information were selected for this review. The most challenging task for AI in such healthcare sectors is to sustain its adoption in daily clinical practice, regardless of whether the programs are scalable enough to be useful. Based on the summarized data, it has been concluded that AI can assist healthcare staff in expanding their knowledge, allowing them to spend more time providing direct patient care and reducing weariness. Overall, we might conclude that the future of "conventional medicine" is closer than we realize, with patients seeing a computer first and subsequently a doctor.
人工智能(AI)被认为是人类可利用的极其有效且前景广阔的科学工具之一。人工智能及其相关创新在工业和文化领域正变得越来越流行,并且开始在医疗保健领域崭露头角。这些创新可能会改变医疗保健的诸多方面,以及医疗服务提供者、支付方和制药公司内部的监管程序。因此,本综述的目的是确定机器学习在传染病领域和一般医疗系统中的潜在应用。关于该主题的文献从各种数据库中提取,如谷歌、谷歌学术、PubMed、Scopus和科学网。选取了具有重要信息的文章用于本综述。在这样的医疗保健领域,人工智能面临的最具挑战性的任务是在日常临床实践中持续应用,无论这些程序是否具有足够的可扩展性以发挥作用。根据汇总的数据得出结论,人工智能可以帮助医护人员扩展知识,使他们有更多时间提供直接的患者护理并减轻疲劳。总体而言,我们可以得出结论,“传统医学”的未来比我们意识到的更近,患者首先见到的将是计算机,随后才是医生。