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 …

Clinical information retrieval (IR) plays a vital role in modern healthcare by facilitating
efficient access and analysis of medical literature for clinicians and researchers. This …

Background The electronic health record (EHR) contains a wealth of medical information. An
organized EHR can greatly help doctors treat patients. In some cases, only limited patient …

Background This study addresses the challenge of enhancing Retrieval Augmented
Generation (RAG) search engines for electronic medical records (EMR) by learning users' …

Pain has been an area of growing interest in the past decade and is known to be associated
with mental health issues. Due to the ambiguous nature of how pain is described in text, it …

Background Information retrieval (IR) help clinicians answer questions posed to large
collections of electronic medical records (EMRs), such as how best to identify a patient's …

Biological information are continuously analyzed and collected by health-informatics tools
for knowledge extraction. For instance, Next Generation Sequencing (NGS) and Micro Array …

Objective A large amount of clinical data are stored in clinical notes that frequently contain
spelling variations, typos, local practice-generated acronyms, synonyms, and informal …

Objective Little research has been done on the user-centered document ranking approach,
especially in a crowdsourcing chart review environment. As the starting point of designing …

Entity retrieval plays a crucial role in the utilization of Electronic Health Records (EHRs) and
is applied across a wide range of clinical practices. However, a comprehensive evaluation of …