[HTML][HTML] Clinical text data in machine learning: systematic review
Background: Clinical narratives represent the main form of communication within health
care, providing a personalized account of patient history and assessments, and offering rich …
care, providing a personalized account of patient history and assessments, and offering rich …
Deep learning in clinical natural language processing: a methodical review
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 …
language processing (NLP) in the clinical domain, providing quantitative analysis to answer …
[HTML][HTML] Chinese clinical named entity recognition with variant neural structures based on BERT methods
Abstract Clinical Named Entity Recognition (CNER) is a critical task which aims to identify
and classify clinical terms in electronic medical records. In recent years, deep neural …
and classify clinical terms in electronic medical records. In recent years, deep neural …
[HTML][HTML] Translating cancer genomics into precision medicine with artificial intelligence: applications, challenges and future perspectives
J Xu, P Yang, S Xue, B Sharma, M Sanchez-Martin… - Human genetics, 2019 - Springer
In the field of cancer genomics, the broad availability of genetic information offered by next-
generation sequencing technologies and rapid growth in biomedical publication has led to …
generation sequencing technologies and rapid growth in biomedical publication has led to …
Deep learning methods for biomedical named entity recognition: a survey and qualitative comparison
The biomedical literature is growing rapidly, and the extraction of meaningful information
from the large amount of literature is increasingly important. Biomedical named entity …
from the large amount of literature is increasingly important. Biomedical named entity …
[HTML][HTML] A survey on recent named entity recognition and relationship extraction techniques on clinical texts
Significant growth in Electronic Health Records (EHR) over the last decade has provided an
abundance of clinical text that is mostly unstructured and untapped. This huge amount of …
abundance of clinical text that is mostly unstructured and untapped. This huge amount of …
[HTML][HTML] Information extraction from electronic medical documents: state of the art and future research directions
MY Landolsi, L Hlaoua, L Ben Romdhane - Knowledge and Information …, 2023 - Springer
In the medical field, a doctor must have a comprehensive knowledge by reading and writing
narrative documents, and he is responsible for every decision he takes for patients …
narrative documents, and he is responsible for every decision he takes for patients …
Crosslingual named entity recognition for clinical de-identification applied to a COVID-19 Italian data set
Abstract The COrona VIrus Disease 19 (COVID-19) pandemic required the work of all global
experts to tackle it. Despite the abundance of new studies, privacy laws prevent their …
experts to tackle it. Despite the abundance of new studies, privacy laws prevent their …
Universalner: Targeted distillation from large language models for open named entity recognition
Large language models (LLMs) have demonstrated remarkable generalizability, such as
understanding arbitrary entities and relations. Instruction tuning has proven effective for …
understanding arbitrary entities and relations. Instruction tuning has proven effective for …
Biomedical named entity recognition at scale
Named entity recognition (NER) is a widely applicable natural language processing task
and building block of question answering, topic modeling, information retrieval, etc. In the …
and building block of question answering, topic modeling, information retrieval, etc. In the …