[HTML][HTML] Clinical concept extraction: a methodology review
Background Concept extraction, a subdomain of natural language processing (NLP) with a
focus on extracting concepts of interest, has been adopted to computationally extract clinical …
focus on extracting concepts of interest, has been adopted to computationally extract clinical …
Extracting information from textual documents in the electronic health record: a review of recent research
SM Meystre, GK Savova… - Yearbook of medical …, 2008 - thieme-connect.com
Objectives We examine recent published research on the extraction of information from
textual documents in the Electronic Health Record (EHR). Methods Literature review of the …
textual documents in the Electronic Health Record (EHR). Methods Literature review of the …
Identifying patient smoking status from medical discharge records
The authors organized a Natural Language Processing (NLP) challenge on automatically
determining the smoking status of patients from information found in their discharge records …
determining the smoking status of patients from information found in their discharge records …
Model tuning or prompt Tuning? a study of large language models for clinical concept and relation extraction
Objective To develop soft prompt-based learning architecture for large language models
(LLMs), examine prompt-tuning using frozen/unfrozen LLMs, and assess their abilities in …
(LLMs), examine prompt-tuning using frozen/unfrozen LLMs, and assess their abilities in …
Automatic identification of heart failure diagnostic criteria, using text analysis of clinical notes from electronic health records
RJ Byrd, SR Steinhubl, J Sun, S Ebadollahi… - International journal of …, 2014 - Elsevier
Abstract Objective Early detection of Heart Failure (HF) could mitigate the enormous
individual and societal burden from this disease. Clinical detection is based, in part, on …
individual and societal burden from this disease. Clinical detection is based, in part, on …
ICD-9 tobacco use codes are effective identifiers of smoking status
Objective To evaluate the validity of, characterize the usage of, and propose potential
research applications for International Classification of Diseases, Ninth Revision (ICD-9) …
research applications for International Classification of Diseases, Ninth Revision (ICD-9) …
Using machine learning for concept extraction on clinical documents from multiple data sources
Objective Concept extraction is a process to identify phrases referring to concepts of
interests in unstructured text. It is a critical component in automated text processing. We …
interests in unstructured text. It is a critical component in automated text processing. We …
Machine learning applications in tobacco research: a scoping review
Objective Identify and review the body of tobacco research literature that self-identified as
using machine learning (ML) in the analysis. Data sources MEDLINE, EMABSE, PubMed …
using machine learning (ML) in the analysis. Data sources MEDLINE, EMABSE, PubMed …
Extracting diagnoses and investigation results from unstructured text in electronic health records by semi-supervised machine learning
Background Electronic health records are invaluable for medical research, but much of the
information is recorded as unstructured free text which is time-consuming to review …
information is recorded as unstructured free text which is time-consuming to review …
N-gram support vector machines for scalable procedure and diagnosis classification, with applications to clinical free text data from the intensive care unit
Background Existing risk adjustment models for intensive care unit (ICU) outcomes rely on
manual abstraction of patient-level predictors from medical charts. Developing an automated …
manual abstraction of patient-level predictors from medical charts. Developing an automated …