ArticleMethods of information in medicine2016
Valx: A System for Extracting and Structuring Numeric Lab Test Comparison Statements from Text.
Article in Methods of information in medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 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
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Using Natural Language Processing to Measure and Improve Quality of Diabetes Care: A Systematic Review.Journal of diabetes science and technology · 2021Pooled it
- Harmonizing Logical Observation Identifiers Names and Codes (LOINC) Codes and Units in Real-World Oncology Data: Method Development and Evaluation.JMIR medical informatics · 2026Article
- Parsing Clinical Trial Eligibility Criteria for Cohort Query by a Multi-Input Multi-Output Sequence Labeling Model.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2023Article
- Combining human and machine intelligence for clinical trial eligibility querying.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- ELaPro, a LOINC-mapped core dataset for top laboratory procedures of eligibility screening for clinical trials.BMC medical research methodology · 2022Article
- Transformer-Based Named Entity Recognition for Parsing Clinical Trial Eligibility Criteria.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2021Article
- How the clinical research community responded to the COVID-19 pandemic: an analysis of the COVID-19 clinical studies in ClinicalTrials.gov.JAMIA open · 2021Article
- How the clinical research community responded to the COVID-19 pandemic: An analysis of the COVID-19 clinical studies in ClinicalTrials.gov.medRxiv : the preprint server for health sciences · 2020Article
- Retrieving Lab Test Related Questions from Social Q&A Sites by Combining Shallow Features and Deep Representations.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2020Article
- DQueST: dynamic questionnaire for search of clinical trials.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- Quantifying risk factors in medical reports with a context-aware linear model.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- Criteria2Query: a natural language interface to clinical databases for cohort definition.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- Comparing the Study Populations in Dietary Supplement and Drug Clinical Trials for Metabolic Syndrome and Related Disorders.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019Article
- A bibliometric analysis of natural language processing in medical research.BMC medical informatics and decision making · 2018Article
- A pattern learning-based method for temporal expression extraction and normalization from multi-lingual heterogeneous clinical texts.BMC medical informatics and decision making · 2018Article
- The representativeness of eligible patients in type 2 diabetes trials: a case study using GIST 2.0.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Clinical information extraction applications: A literature review.Journal of biomedical informatics · 2018Review
- EliIE: An open-source information extraction system for clinical trial eligibility criteria.Journal of the American Medical Informatics Association : JAMIA · 2017Article
- An OMOP CDM-Based Relational Database of Clinical Research Eligibility Criteria.Studies in health technology and informatics · 2017Article
- Comparing and Contrasting A Priori and A Posteriori Generalizability Assessment of Clinical Trials on Type 2 Diabetes Mellitus.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2017Article
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
objectivesTo develop an automated method for extracting and structuring numeric lab test comparison statements from text and evaluate the method using clinical trial eligibility criteria text.
methodsLeveraging semantic knowledge from the Unified Medical Language System (UMLS) and domain knowledge acquired from the Internet, Valx takes seven steps to extract and normalize numeric lab test expressions: 1) text preprocessing, 2) numeric, unit, and comparison operator extraction, 3) variable identification using hybrid knowledge, 4) variable - numeric association, 5) context-based association filtering, 6) measurement unit normalization, and 7) heuristic rule-based comparison statements verification. Our reference standard was the consensus-based annotation among three raters for all comparison statements for two variables, i.e., HbA1c and glucose, identified from all of Type 1 and Type 2 diabetes trials in ClinicalTrials.gov.
resultsThe precision, recall, and F-measure for structuring HbA1c comparison statements were 99.6%, 98.1%, 98.8% for Type 1 diabetes trials, and 98.8%, 96.9%, 97.8% for Type 2 diabetes trials, respectively. The precision, recall, and F-measure for structuring glucose comparison statements were 97.3%, 94.8%, 96.1% for Type 1 diabetes trials, and 92.3%, 92.3%, 92.3% for Type 2 diabetes trials, respectively.
conclusionsValx is effective at extracting and structuring free-text lab test comparison statements in clinical trial summaries. Future studies are warranted to test its generalizability beyond eligibility criteria text. The open-source Valx enables its further evaluation and continued improvement among the collaborative scientific community.
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.