SynthesisJournal of the American Medical Informatics Association : JAMIA2021
A systematic review of automatic text summarization for biomedical literature and EHRs.
Synthesis in Journal of the American Medical Informatics Association : JAMIA, 2021. 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.
- Increasing Women's Knowledge about HPV Using BERT Text Summarization: An Online Randomized Study.International journal of environmental research and public health · 2022Trial
- Patient-Centered Summarization Framework for AI Clinical Summarization: Mixed Methods Study.Journal of medical Internet research · 2026Article
- Article
- Assessing genetic counseling efficiency with natural language processing.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Leveraging artificial intelligence to reduce diagnostic errors in emergency medicine: Challenges, opportunities, and future directions.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2025Review
- Correspondence on "Optimizing ChatGPT's Performance in Hypertension Care".Journal of clinical hypertension (Greenwich, Conn.) · 2025Article
- Leveraging artificial intelligence to summarize abstracts in lay language for increasing research accessibility and transparency.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Harnessing EHR data for health research.Nature medicine · 2024Review
- The power of graphs in medicine: Introducing BioGraphSum for effective text summarization.Heliyon · 2024Article
- Evaluation of a Digital Scribe: Conversation Summarization for Emergency Department Consultation Calls.Applied clinical informatics · 2024Article
- SPeC: A Soft Prompt-Based Calibration on Performance Variability of Large Language Model in Clinical Notes Summarization.Journal of biomedical informatics · 2024Article
- Prospects for AI clinical summarization to reduce the burden of patient chart review.Frontiers in digital health · 2024Review
- Retrieval augmentation of large language models for lay language generation.Journal of biomedical informatics · 2024Article
- Information Capsule: A New Approach for Summarizing Medical Information.International journal of preventive medicine · 2024Article
- An LLM-Powered Clinical Calculator Chatbot Backed by Verifiable Clinical Calculators and their Metadata.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Development and Evaluation of a Digital Scribe: Conversation Summarization Pipeline for Emergency Department Counseling Sessions towards Reducing Documentation Burden.medRxiv : the preprint server for health sciences · 2023Article
- Patient Information Summarization in Clinical Settings: Scoping Review.JMIR medical informatics · 2023Article
- Leveraging the potential of synthetic text for AI in mental healthcare.Frontiers in digital health · 2022Article
- Computational Analyses Reveal Fundamental Properties of the Hemophilia Literature in the Last 6 Decades.Bioinformatics and biology insights · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveBiomedical text summarization helps biomedical information seekers avoid information overload by reducing the length of a document while preserving the contents' essence. Our systematic review investigates the most recent biomedical text summarization researches on biomedical literature and electronic health records by analyzing their techniques, areas of application, and evaluation methods. We identify gaps and propose potential directions for future research. MATERIALS AND
methodsThis review followed the PRISMA methodology and replicated the approaches adopted by the previous systematic review published on the same topic. We searched 4 databases (PubMed, ACM Digital Library, Scopus, and Web of Science) from January 1, 2013 to April 8, 2021. Two reviewers independently screened title, abstract, and full-text for all retrieved articles. The conflicts were resolved by the third reviewer. The data extraction of the included articles was in 5 dimensions: input, purpose, output, method, and evaluation.
resultsFifty-eight out of 7235 retrieved articles met the inclusion criteria. Thirty-nine systems used single-document biomedical research literature as their input, 17 systems were explicitly designed for clinical support, 47 systems generated extractive summaries, and 53 systems adopted hybrid methods combining computational linguistics, machine learning, and statistical approaches. As for the assessment, 51 studies conducted an intrinsic evaluation using predefined metrics. DISCUSSION AND
conclusionThis study found that current biomedical text summarization systems have achieved good performance using hybrid methods. Studies on electronic health records summarization have been increasing compared to a previous survey. However, the majority of the works still focus on summarizing literature.
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.