[HTML][HTML] Machine learning and natural language processing in mental health: systematic review
A Le Glaz, Y Haralambous, DH Kim-Dufor… - Journal of medical …, 2021 - jmir.org
Background Machine learning systems are part of the field of artificial intelligence that
automatically learn models from data to make better decisions. Natural language processing …
automatically learn models from data to make better decisions. Natural language processing …
A narrative review on the validity of electronic health record-based research in epidemiology
MA Gianfrancesco, ND Goldstein - BMC medical research methodology, 2021 - Springer
Electronic health records (EHRs) are widely used in epidemiological research, but the
validity of the results is dependent upon the assumptions made about the healthcare system …
validity of the results is dependent upon the assumptions made about the healthcare system …
Cohort profile of the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLaM BRC) case register: current status and recent …
Purpose The South London and Maudsley National Health Service (NHS) Foundation Trust
Biomedical Research Centre (SLaM BRC) Case Register and its Clinical Record Interactive …
Biomedical Research Centre (SLaM BRC) Case Register and its Clinical Record Interactive …
Natural language processing for EHR-based computational phenotyping
This article reviews recent advances in applying natural language processing (NLP) to
Electronic Health Records (EHRs) for computational phenotyping. NLP-based …
Electronic Health Records (EHRs) for computational phenotyping. NLP-based …
A systematic review of natural language processing for classification tasks in the field of incident reporting and adverse event analysis
Context Adverse events in healthcare are often collated in incident reports which contain
unstructured free text. Learning from these events may improve patient safety. Natural …
unstructured free text. Learning from these events may improve patient safety. Natural …
Natural language processing for EHR-based pharmacovigilance: a structured review
The goal of pharmacovigilance is to detect, monitor, characterize and prevent adverse drug
events (ADEs) with pharmaceutical products. This article is a comprehensive structured …
events (ADEs) with pharmaceutical products. This article is a comprehensive structured …
SemEHR: A general-purpose semantic search system to surface semantic data from clinical notes for tailored care, trial recruitment, and clinical research
Objective Unlocking the data contained within both structured and unstructured components
of electronic health records (EHRs) has the potential to provide a step change in data …
of electronic health records (EHRs) has the potential to provide a step change in data …
[HTML][HTML] Capturing the patient's perspective: a review of advances in natural language processing of health-related text
G Gonzalez-Hernandez, A Sarker… - Yearbook of medical …, 2017 - thieme-connect.com
Background: Natural Language Processing (NLP) methods are increasingly being utilized to
mine knowledge from unstructured health-related texts. Recent advances in noisy text …
mine knowledge from unstructured health-related texts. Recent advances in noisy text …
Knowledge graph prediction of unknown adverse drug reactions and validation in electronic health records
Unknown adverse reactions to drugs available on the market present a significant health risk
and limit accurate judgement of the cost/benefit trade-off for medications. Machine learning …
and limit accurate judgement of the cost/benefit trade-off for medications. Machine learning …
Named entity recognition in electronic health records using transfer learning bootstrapped neural networks
Neural networks (NNs) have become the state of the art in many machine learning
applications, such as image, sound (LeCun et al., 2015) and natural language processing …
applications, such as image, sound (LeCun et al., 2015) and natural language processing …