REVIEW ON MACHINE LEARNING

artificial intelligence

Numerous real-world data sources are made available by the extensive usage of electronic health record (EHR) systems in the medical field, opening up new directions for clinical research. Due to the fact that clinical narratives in electronic health records include a significant quantity of important clinical information, natural language processing (NLP) techniques have been employed as an artificial intelligence strategy to extract information from them. However, much clinical facts are still concealed in a clinical narrative structure in free-form texts like electronic health records. Consequently, to fully utilize EHR data and automatically transform clinical narrative text into structured clinical data, biomedical NLP algorithms must be used. Biomedical NLP applications might thus be utilized to guide clinical judgments, recognize health issues, and successfully prevent or delay the onset of a disease. This review analyzes the possibilities, difficulties, and uses of biomedical natural language processing (NLP) techniques and examines the literature that is currently available on the secondary use of electronic health record data for clinical research on chronic diseases. We provide an overview of machine learning and deep learning techniques used to process EHRs and enhance the comprehension of the patient's clinical records and the prediction of chronic disease risk. These techniques offer a great opportunity to extract previously undiscovered clinical information. We also review some of the biomedical NLP systems and methods used over EHRs. Additionally, based on EHR data relevant to chronic diseases, this research describes the application of Deep Learning and Machine Learning algorithms in biomedical NLP applications. In conclusion, this evaluation showcases the future trends and challenges in the biomedical NLP. INDEX TERMS: machine learning, natural language processing (NLP), clinical data, deep learning, artificial intelligence (AI), and electronic health records (EHR).

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