Advances in electronic health records enabled by artificial intelligence and natural language processing: a review of recent developments, limitations and future applications

Abstract

AI is a powerful and predictive technique, with the possible to mostly transform the preparation of medication and classifications of electronic health records in healthcare. The main focus of this article is to summarize, finding out the significance, limitations, and future applications of artificial intelligence in healthcare domains, and study AI techniques and NLP procedures that are used for healthcare document processing. This review follows the PRISMA guidelines to find recent and related to the current AI and NLP techniques in healthcare. The search was done through using 5 databases (Science Direct, PubMed, Web of Science, Scopus, and Google Scholar) with keywords AI in healthcare, NLP for healthcare, ML for EHRs, medical applications of AI, and challenges of AI in EHRs. We selected a total of 306 initial papers, of which 22 (7.1%) were included and 284 (92.9%) excluded in this review. Recent developments in AI are extensively studied. AI and NLP techniques have been extremely interesting issues in healthcare in recent years, and it is considered a new paradigm in the medical research in enhancing decision-making and more accessible healthcare services. According to this report, AI applications should play an imperative role in enabling the efficient use of and analysis of vast amounts of healthcare and medical records, as well as identifying the problems associated with processing languages that have limited resources. These reviews lastly deal with the importance, limitations, and prospects of the development of AI technologies in processing EHRs in healthcare.

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