SynthesisYearbook of medical informatics2015
Clinical Natural Language Processing in 2014: Foundational Methods Supporting Efficient Healthcare.
Synthesis in Yearbook of medical informatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed.
- Article
- Predicting Kidney Transplant Recipient Cohorts' 30-Day Rehospitalization Using Clinical Notes and Electronic Health Care Record Data.Kidney international reports · 2023Article
- Performance of ChatGPT-4 in answering questions from the Brazilian National Examination for Medical Degree Revalidation.Revista da Associacao Medica Brasileira (1992) · 2023Article
- An ensemble approach for healthcare application and diagnosis using natural language processing.Cognitive neurodynamics · 2022Article
- Classifying the lifestyle status for Alzheimer's disease from clinical notes using deep learning with weak supervision.BMC medical informatics and decision making · 2022Article
- Exploring Sentiment and Care Management of Hospitalized Patients During the First Wave of the COVID-19 Pandemic Using Electronic Nursing Health Records: Descriptive Study.JMIR medical informatics · 2022Article
- Assessing the Performance of Clinical Natural Language Processing Systems: Development of an Evaluation Methodology.JMIR medical informatics · 2021Article
- Should free-text data in electronic medical records be shared for research? A citizens' jury study in the UK.Journal of medical ethics · 2020Article
- Natural Language Processing Combined with ICD-9-CM Codes as a Novel Method to Study the Epidemiology of Allergic Drug Reactions.The journal of allergy and clinical immunology. In practice · 2020Article
- Customization scenarios for de-identification of clinical notes.BMC medical informatics and decision making · 2020Article
- Systematic Evaluation of Research Progress on Natural Language Processing in Medicine Over the Past 20 Years: Bibliometric Study on PubMed.Journal of medical Internet research · 2020Review
- Evaluating the Portability of an NLP System for Processing Echocardiograms: A Retrospective, Multi-site Observational Study.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2019Observational
- Risk Assessment Tools and Data-Driven Approaches for Predicting and Preventing Suicidal Behavior.Frontiers in psychiatry · 2019Article
- Using clinical Natural Language Processing for health outcomes research: Overview and actionable suggestions for future advances.Journal of biomedical informatics · 2018Article
- Clinical Natural Language Processing in languages other than English: opportunities and challenges.Journal of biomedical semantics · 2018Review
- From Sour Grapes to Low-Hanging Fruit: A Case Study Demonstrating a Practical Strategy for Natural Language Processing Portability.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2018Article
- Capturing the Patient's Perspective: a Review of Advances in Natural Language Processing of Health-Related Text.Yearbook of medical informatics · 2017Review
- Aspiring to Unintended Consequences of Natural Language Processing: A Review of Recent Developments in Clinical and Consumer-Generated Text Processing.Yearbook of medical informatics · 2016Review
- Automatic classification of registered clinical trials towards the Global Burden of Diseases taxonomy of diseases and injuries.BMC bioinformatics · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo summarize recent research and present a selection of the best papers published in 2014 in the field of clinical Natural Language Processing (NLP).
methodA systematic review of the literature was performed by the two section editors of the IMIA Yearbook NLP section by searching bibliographic databases with a focus on NLP efforts applied to clinical texts or aimed at a clinical outcome. A shortlist of candidate best papers was first selected by the section editors before being peer-reviewed by independent external reviewers.
resultsThe clinical NLP best paper selection shows that the field is tackling text analysis methods of increasing depth. The full review process highlighted five papers addressing foundational methods in clinical NLP using clinically relevant texts from online forums or encyclopedias, clinical texts from Electronic Health Records, and included studies specifically aiming at a practical clinical outcome. The increased access to clinical data that was made possible with the recent progress of de-identification paved the way for the scientific community to address complex NLP problems such as word sense disambiguation, negation, temporal analysis and specific information nugget extraction. These advances in turn allowed for efficient application of NLP to clinical problems such as cancer patient triage. Another line of research investigates online clinically relevant texts and brings interesting insight on communication strategies to convey health-related information.
conclusionsThe field of clinical NLP is thriving through the contributions of both NLP researchers and healthcare professionals interested in applying NLP techniques for concrete healthcare purposes. Clinical NLP is becoming mature for practical applications with a significant clinical impact.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.