ArticleBMC medical informatics and decision making2019
An open access medical knowledge base for community driven diagnostic decision support system development.
Article in BMC medical informatics and decision making, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled 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
- Effects of a Differential Diagnosis List of Artificial Intelligence on Differential Diagnoses by Physicians: An Exploratory Analysis of Data from a Randomized Controlled Study.International journal of environmental research and public health · 2021Trial
- Development and prospective implementation of a large language model based system for early sepsis prediction.NPJ digital medicine · 2025Article
- Development and Prospective Implementation of a Large Language Model based System for Early Sepsis Prediction.medRxiv : the preprint server for health sciences · 2025Article
- Retrieval-Based Diagnostic Decision Support: Mixed Methods Study.JMIR medical informatics · 2024Article
- DRGKB: a knowledgebase of worldwide diagnosis-related groups' practices for comparison, evaluation and knowledge-guided application.Database : the journal of biological databases and curation · 2024Article
- HTNpedia: A Knowledge Base for Hypertension Research.Combinatorial chemistry & high throughput screening · 2024Article
- Multidisciplinary Development and Initial Validation of a Clinical Knowledge Base on Chronic Respiratory Diseases for mHealth Decision Support Systems.Journal of medical Internet research · 2023Observational
- Harnessing the power of clinical decision support systems: challenges and opportunities.Open heart · 2023Review
- Artificial intelligence in clinical decision support systems for oncology.International journal of medical sciences · 2023Review
- Assessing the Performance of a New Artificial Intelligence-Driven Diagnostic Support Tool Using Medical Board Exam Simulations: Clinical Vignette Study.JMIR medical informatics · 2021Article
- The use of SNOMED CT, 2013-2020: a literature review.Journal of the American Medical Informatics Association : JAMIA · 2021Review
- Pragmatic Considerations on Clinical Decision Support from the 2019 Literature.Yearbook of medical informatics · 2020Review
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
introductionWhile early diagnostic decision support systems were built around knowledge bases, more recent systems employ machine learning to consume large amounts of health data. We argue curated knowledge bases will remain an important component of future diagnostic decision support systems by providing ground truth and facilitating explainable human-computer interaction, but that prototype development is hampered by the lack of freely available computable knowledge bases.
methodsWe constructed an open access knowledge base and evaluated its potential in the context of a prototype decision support system. We developed a modified set-covering algorithm to benchmark the performance of our knowledge base compared to existing platforms. Testing was based on case reports from selected literature and medical student preparatory material.
resultsThe knowledge base contains over 2000 ICD-10 coded diseases and 450 RX-Norm coded medications, with over 8000 unique observations encoded as SNOMED or LOINC semantic terms. Using 117 medical cases, we found the accuracy of the knowledge base and test algorithm to be comparable to established diagnostic tools such as Isabel and DXplain. Our prototype, as well as DXplain, showed the correct answer as "best suggestion" in 33% of the cases. While we identified shortcomings during development and evaluation, we found the knowledge base to be a promising platform for decision support systems.
conclusionWe built and successfully evaluated an open access knowledge base to facilitate the development of new medical diagnostic assistants. This knowledge base can be expanded and curated by users and serve as a starting point to facilitate new technology development and system improvement in many contexts.
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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.