ArticleStudies in health technology and informatics2019
Pretraining to Recognize PICO Elements from Randomized Controlled Trial Literature.
Article in Studies in health technology and informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 3 of them syntheses that pooled it.
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
22 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Effects of Digital Physical Health Exercises on Musculoskeletal Diseases: Systematic Review With Best-Evidence Synthesis.JMIR mHealth and uHealth · 2024Pooled it
- Psychological Effects of Online-Based Mindfulness Programs during the COVID-19 Pandemic: A Systematic Review of Randomized Controlled Trials.International journal of environmental research and public health · 2022Pooled it
- Data extraction methods for systematic review (semi)automation: Update of a living systematic review.F1000Research · 2021Pooled it
- A span-based model for extracting overlapping PICO entities from randomized controlled trial publications.Journal of the American Medical Informatics Association : JAMIA · 2024Trial
- EvidenceMap: a three-level knowledge representation for medical evidence computation and comprehension.Journal of the American Medical Informatics Association : JAMIA · 2023Trial
- Evaluating Methodological Coherence and Evidence Recognition in Digital Health Systematic Reviews: Sample-based Meta-research Study.Online journal of public health informatics · 2026Review
- PICO-based assessment and categorization of evidence for digital health interventions: an inductive framework development.Frontiers in digital health · 2026Review
- Evaluation of SURUS: a named entity recognition NLP system to extract knowledge from interventional study records.BMC medical research methodology · 2025Article
- Natural Language Processing in Support of Evidence-based Medicine: A Scoping Review.Findings of ACL. ACL · 2025Article
- Critical Analysis of Reporting Quality of Network Meta-Analyses in Periodontology and Implantology.European journal of dentistry · 2025Article
- Digital Health Interventions Targeting Psychological Health in Parents of Children With Autism Spectrum Disorder: Protocol for a Scoping Review.JMIR research protocols · 2025Article
- Efficient evidence selection for systematic reviews in traditional Chinese medicine.BMC medical research methodology · 2025Article
- PICOT questions and search strategies formulation: A novel approach using artificial intelligence automation.Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2025Article
- Using Digital Media to Improve Adolescent Resilience and Prevent Mental Health Problems: Protocol for a Scoping Review.JMIR research protocols · 2024Article
- Comparing generative and extractive approaches to information extraction from abstracts describing randomized clinical trials.Journal of biomedical semantics · 2024Article
- Automatic categorization of self-acknowledged limitations in randomized controlled trial publications.Journal of biomedical informatics · 2024Article
- Towards precise PICO extraction from abstracts of randomized controlled trials using a section-specific learning approach.Bioinformatics (Oxford, England) · 2023Article
- A pipeline for the retrieval and extraction of domain-specific information with application to COVID-19 immune signatures.BMC bioinformatics · 2023Article
- Identifying and Analyzing Topic Clusters in a Nutri-, Food-, and Diet-Proteomic Corpus Using Machine Reading.Nutrients · 2023Review
- A Scoping Review of Adopted Information Extraction Methods for RCTs.Medical journal of the Islamic Republic of Iran · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
PICO (Population/problem, Intervention, Comparison, and Outcome) is widely adopted for formulating clinical questions to retrieve evidence from the literature. It plays a crucial role in Evidence-Based Medicine (EBM). This paper contributes a scalable deep learning method to extract PICO statements from RCT articles. It was trained on a small set of richly annotated PubMed abstracts using an LSTM-CRF model. By initializing our model with pretrained parameters from a large related corpus, we improved the model performance significantly with a minimal feature set. Our method has advantages in minimizing the need for laborious feature handcrafting and in avoiding the need for large shared annotated data by reusing related corpora in pretraining with a deep neural network.
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.