ArticleApplied clinical informatics2018
Artificial Intelligence: Bayesian versus Heuristic Method for Diagnostic Decision Support.
Article in Applied clinical informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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
12 citing papers in PubMed, 40 citations in OpenAlex.
- Artificial intelligence and machine learning in sports medicine: mapping clinical tasks and assessing clinical maturity - a scoping review.BMC medical informatics and decision making · 2026Article
- The Rise of Artificial Intelligence in Orthopedics: A Bibliometric and Visualization Analysis.Journal of multidisciplinary healthcare · 2025Article
- How Will Artificial Intelligence Shape the Future of Decision-Making in Congenital Heart Disease?Journal of clinical medicine · 2024Review
- Digital Health Applications to Establish a Remote Diagnosis of Orthopedic Knee Disorders: Scoping Review.Journal of medical Internet research · 2023Article
- An artificially intelligent (or algorithm-enhanced) electronic medical record in orofacial pain.The Japanese dental science review · 2021Review
- Model Construction and Research on Decision Support System for Education Management Based on Data Mining.Computational intelligence and neuroscience · 2021Article
- [Challenges of digitalization in trauma care].Der Unfallchirurg · 2020Review
- Impact of industry 4.0 to create advancements in orthopaedics.Journal of clinical orthopaedics and trauma · 2020Article
- [Artificial intelligence in orthopedics and trauma surgery].Der Chirurg; Zeitschrift fur alle Gebiete der operativen Medizen · 2020Review
- Artificial Intelligence (AI) applications in orthopaedics: An innovative technology to embrace.Journal of clinical orthopaedics and trauma · 2020Article
- Sustainable Health Informatics: Health Informaticians as Alchemists.Studies in health technology and informatics · 2019Article
- Artificial Intelligence in Clinical Decision Support: a Focused Literature Survey.Yearbook of medical informatics · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Evoking strength is one of the important contributions of the field of Biomedical Informatics to the discipline of Artificial Intelligence. The University at Buffalo's Orthopedics Department wanted to create an expert system to assist patients with self-diagnosis of knee problems and to thereby facilitate referral to the right orthopedic subspecialist. They had two independent sports medicine physicians review 469 cases. A board-certified orthopedic sports medicine practitioner, L.B., reviewed any disagreements until a gold standard diagnosis was reached. For each case, the patients entered 126 potential answers to 26 questions into a Web interface. These were modeled by an expert sports medicine physician and the answers were reviewed by L.B. For each finding, the clinician specified the sensitivity (term frequency) and both specificity (Sp) and the heuristic evoking strength (ES). Heuristics are methods of reasoning with only partial evidence. An expert system was constructed that reflected the posttest odds of disease-ranked list for each case. We compare the accuracy of using Sp to that of using ES (original model,
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.