ArticleBriefings in bioinformatics2018
Biomedical text mining for research rigor and integrity: tasks, challenges, directions.
Article in Briefings in bioinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis 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
35 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Large Language Model Analysis of Reporting Quality of Randomized Clinical Trial Articles: A Systematic Review.JAMA network open · 2025Pooled it
- Auditing frontier general-purpose large language models in biomedical tasks: reasoning gains, extraction limits, and benchmark reliability.Research square · 2026Article
- Enhancing Healthcare Integrity Using Simple Statistical Methods: Detecting Irregularities in Historical Dermatology Services Payments.Healthcare (Basel, Switzerland) · 2025Article
- SPIRIT-CONSORT-TM: a corpus for assessing transparency of clinical trial protocol and results publications.Scientific data · 2025Article
- SPIRIT-CONSORT-TM: a corpus for assessing transparency of clinical trial protocol and results publications.medRxiv : the preprint server for health sciences · 2025Article
- Text classification models for assessing the completeness of randomized controlled trial publications based on CONSORT reporting guidelines.Scientific reports · 2024Article
- Assessing citation integrity in biomedical publications: corpus annotation and NLP models.Bioinformatics (Oxford, England) · 2024Article
- Automatic categorization of self-acknowledged limitations in randomized controlled trial publications.Journal of biomedical informatics · 2024Article
- CONSORT-TM: Text classification models for assessing the completeness of randomized controlled trial publications.medRxiv : the preprint server for health sciences · 2024Article
- Asking questions that are "close to the bone": integrating thematic analysis and natural language processing to explore the experiences of people with traumatic brain injuries engaging with patient-reported outcome measures.Frontiers in digital health · 2024Article
- BIR: Biomedical Information Retrieval System for Cancer Treatment in Electronic Health Record Using Transformers.Sensors (Basel, Switzerland) · 2023Article
- NLM-Chem-BC7: manually annotated full-text resources for chemical entity annotation and indexing in biomedical articles.Database : the journal of biological databases and curation · 2022Article
- BioBERT and Similar Approaches for Relation Extraction.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Combining Literature Mining and Machine Learning for Predicting Biomedical Discoveries.Methods in molecular biology (Clifton, N.J.) · 2022Article
- RENET2: high-performance full-text gene-disease relation extraction with iterative training data expansion.NAR genomics and bioinformatics · 2021Article
- Suggesting a framework for preparedness against the pandemic outbreak based on medical informatics solutions: a thematic analysis.The International journal of health planning and management · 2021Article
- Toward assessing clinical trial publications for reporting transparency.Journal of biomedical informatics · 2021Article
- NLM-Chem, a new resource for chemical entity recognition in PubMed full text literature.Scientific data · 2021Article
- Text mining approaches for dealing with the rapidly expanding literature on COVID-19.Briefings in bioinformatics · 2021Review
- Artificial Intelligence Clinical Evidence Engine for Automatic Identification, Prioritization, and Extraction of Relevant Clinical Oncology Research.JCO clinical cancer informatics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An estimated quarter of a trillion US dollars is invested in the biomedical research enterprise annually. There is growing alarm that a significant portion of this investment is wasted because of problems in reproducibility of research findings and in the rigor and integrity of research conduct and reporting. Recent years have seen a flurry of activities focusing on standardization and guideline development to enhance the reproducibility and rigor of biomedical research. Research activity is primarily communicated via textual artifacts, ranging from grant applications to journal publications. These artifacts can be both the source and the manifestation of practices leading to research waste. For example, an article may describe a poorly designed experiment, or the authors may reach conclusions not supported by the evidence presented. In this article, we pose the question of whether biomedical text mining techniques can assist the stakeholders in the biomedical research enterprise in doing their part toward enhancing research integrity and rigor. In particular, we identify four key areas in which text mining techniques can make a significant contribution: plagiarism/fraud detection, ensuring adherence to reporting guidelines, managing information overload and accurate citation/enhanced bibliometrics. We review the existing methods and tools for specific tasks, if they exist, or discuss relevant research that can provide guidance for future work. With the exponential increase in biomedical research output and the ability of text mining approaches to perform automatic tasks at large scale, we propose that such approaches can support tools that promote responsible research practices, providing significant benefits for the biomedical research enterprise.
Indexed as
Identifiers
What Socratic 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 Socratic graph.