ArticleJournal of the American Medical Informatics Association : JAMIA
Clinical decision support with automated text processing for cervical cancer screening.
Article in Journal of the American Medical Informatics Association : JAMIA. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 3 of them syntheses that pooled it.
What it found
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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
46 citing papers in PubMed, 3 syntheses or guidelines pooled it, 85 citations in OpenAlex.
- Clinical Decision Support and Natural Language Processing in Medicine: Systematic Literature Review.Journal of medical Internet research · 2024Pooled it
- Interpretability of Clinical Decision Support Systems Based on Artificial Intelligence from Technological and Medical Perspective: A Systematic Review.Journal of healthcare engineering · 2023Pooled it
- Natural Language Processing Applications in the Clinical Neurosciences: A Machine Learning Augmented Systematic Review.Acta neurochirurgica. Supplement · 2022Pooled it
- Article
- Evaluation of ChatGPT-5-generated clinical management recommendations for HPV infection and cervical premalignant lesions: a scenario-based expert assessment study.BMC medical informatics and decision making · 2026Article
- Identifying Patients with Heart Failure Eligible for Guideline-Directed Medical Therapy.Population health management · 2024Article
- Benefits of Clinical Decision Support Systems for the Management of Noncommunicable Chronic Diseases: Targeted Literature Review.Interactive journal of medical research · 2024Review
- RCC-Supporter: supporting renal cell carcinoma treatment decision-making using machine learning.BMC medical informatics and decision making · 2024Article
- Proposal and Definition of an Intelligent Clinical Decision Support System Applied to the Prediction of Dyspnea after 12 Months of an Acute Episode of COVID-19.Biomedicines · 2024Article
- Article
- Combining text mining with clinical decision support in clinical practice: a scoping review.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Natural Language Processing to Identify Abnormal Breast, Lung, and Cervical Cancer Screening Test Results from Unstructured Reports to Support Timely Follow-up.Studies in health technology and informatics · 2022Article
- Design and Development of an Intelligent Clinical Decision Support System Applied to the Evaluation of Breast Cancer Risk.Journal of personalized medicine · 2022Article
- Validation of rule-based algorithms to determine colorectal, breast, and cervical cancer screening status using electronic health record data from an urban healthcare system in New York City.Preventive medicine reports · 2021Article
- Automatic Classification of Thyroid Findings Using Static and Contextualized Ensemble Natural Language Processing Systems: Development Study.JMIR medical informatics · 2021Article
- Natural Language Processing for Surveillance of Cervical and Anal Cancer and Precancer: Algorithm Development and Split-Validation Study.JMIR medical informatics · 2020Article
- Use of Natural Language Processing Algorithms to Identify Common Data Elements in Operative Notes for Total Hip Arthroplasty.The Journal of bone and joint surgery. American volume · 2019Article
- Compliance with cervical cancer screening guidelines in young female patients: rates and trends of screening in New Haven County, CT.American journal of obstetrics and gynecology · 2019Article
- Association Of Medicare's Annual Wellness Visit With Cancer Screening, Referrals, Utilization, And Spending.Health affairs (Project Hope) · 2019Article
- Automated detection of sudden unexpected death in epilepsy risk factors in electronic medical records using natural language processing.Epilepsia · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
objectiveTo develop a computerized clinical decision support system (CDSS) for cervical cancer screening that can interpret free-text Papanicolaou (Pap) reports. MATERIALS AND
methodsThe CDSS was constituted by two rulebases: the free-text rulebase for interpreting Pap reports and a guideline rulebase. The free-text rulebase was developed by analyzing a corpus of 49 293 Pap reports. The guideline rulebase was constructed using national cervical cancer screening guidelines. The CDSS accesses the electronic medical record (EMR) system to generate patient-specific recommendations. For evaluation, the screening recommendations made by the CDSS for 74 patients were reviewed by a physician. RESULTS AND DISCUSSION: Evaluation revealed that the CDSS outputs the optimal screening recommendations for 73 out of 74 test patients and it identified two cases for gynecology referral that were missed by the physician. The CDSS aided the physician to amend recommendations in six cases. The failure case was because human papillomavirus (HPV) testing was sometimes performed separately from the Pap test and these results were reported by a laboratory system that was not queried by the CDSS. Subsequently, the CDSS was upgraded to look up the HPV results missed earlier and it generated the optimal recommendations for all 74 test cases. LIMITATIONS: Single institution and single expert study.
conclusionAn accurate CDSS system could be constructed for cervical cancer screening given the standardized reporting of Pap tests and the availability of explicit guidelines. Overall, the study demonstrates that free text in the EMR can be effectively utilized through natural language processing to develop clinical decision support tools.
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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.