Abstract Background: Natural Language Processing (NLP) is widely used to extract clinical
insights from Electronic Health Records (EHRs). However, the lack of annotated data …

Smart healthcare has achieved significant progress in recent years. Emerging artificial
intelligence (AI) technologies enable various smart applications across various healthcare …

Clinical notes contain information about patients that goes beyond structured data like lab
values and medications. However, clinical notes have been underused relative to structured …

Background: Clinical narratives represent the main form of communication within health
care, providing a personalized account of patient history and assessments, and offering rich …

Objective This article methodically reviews the literature on deep learning (DL) for natural
language processing (NLP) in the clinical domain, providing quantitative analysis to answer …

Background This research integrates a comparative analysis of the performance of human
researchers and OpenAI's ChatGPT in systematic review tasks and describes an …

Machine learning (ML) has been slowly entering every aspect of our lives and its positive
impact has been astonishing. To accelerate embedding ML in more applications and …

Definition Machine learning (ML) is a study of computer algorithms for automation through
experience. ML is a subset of artificial intelligence (AI) that develops computer systems …

Healthcare institutions are progressively integrating artificial intelligence (AI) into their
operations. The extraordinary potential of AI is restricted by insufficient medical data for AI …

Background Clinical text classification is an fundamental problem in medical natural
language processing. Existing studies have cocnventionally focused on rules or knowledge …