ArticleJournal of medical systems2014
A clinical decision support system with an integrated EMR for diagnosis of peripheral neuropathy.
Article in Journal of medical systems, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 32 citations in OpenAlex.
- Article
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- The Impact of Healthcare Professionals' Characteristics on the Evaluation of Clinical Decision Support Systems: Insights from a Cross-Country Usability and Technology Acceptance Study of the iCARE Tool.Journal of medical systems · 2026Article
- PredictMed-CDSS: Artificial Intelligence-Based Decision Support System Predicting the Probability to Develop Neuromuscular Hip Dysplasia.Bioengineering (Basel, Switzerland) · 2025Article
- Human-AI collectives most accurately diagnose clinical vignettes.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Rising to the Challenge of Rare Diagnoses.Journal of general internal medicine · 2025Article
- Validating the Accuracy of a Patient-Facing Clinical Decision Support System in Predicting Lumbar Disc Herniation: Diagnostic Accuracy Study.Diagnostics (Basel, Switzerland) · 2024Article
- Mobile Diagnostic Clinics.ACS sensors · 2024Review
- Machine learning-based gait adaptation dysfunction identification using CMill-based gait data.Frontiers in neurorobotics · 2024Article
- Expanding access to veterinary clinical decision support in resource-limited settings: a scoping review of clinical decision support tools in medicine and antimicrobial stewardship.Frontiers in veterinary science · 2024Article
- Using Theories, Models, and Frameworks to Inform Implementation Cycles of Computerized Clinical Decision Support Systems in Tertiary Health Care Settings: Scoping Review.Journal of medical Internet research · 2023Article
- Association of Disparities in Family History and Family Cancer History in the Electronic Health Record With Sex, Race, Hispanic or Latino Ethnicity, and Language Preference in 2 Large US Health Care Systems.JAMA network open · 2022Article
- Characteristics of Complex Systems in Sports Injury Rehabilitation: Examples and Implications for Practice.Sports medicine - open · 2022Review
- DZC DIAG: mobile application based on expert system to aid in the diagnosis of dengue, Zika, and chikungunya.Medical & biological engineering & computing · 2020Article
- An overview of clinical decision support systems: benefits, risks, and strategies for success.NPJ digital medicine · 2020Review
- The Application of Medical Artificial Intelligence Technology in Rural Areas of Developing Countries.Health equity · 2018Review
- Opioid prescribing by physicians with and without electronic health records.Journal of medical systems · 2014Article
- The reliability of an epilepsy treatment clinical decision support system.Journal of medical systems · 2014Article
- Developing and using expert systems and neural networks in medicine: a review on benefits and challenges.Journal of medical systems · 2014Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The prevalence of peripheral neuropathy in general population is ever increasing. The diagnosis and classification of peripheral neuropathies is often difficult as it involves careful clinical and electro-diagnostic examination by an expert neurologist. In developing countries a large percentage of the disease remains undiagnosed due to lack of adequate number of experts. In this study a novel clinical decision support system has been developed using a fuzzy expert system. The study was done to provide a solution to the demand of systems that can improve health care by accurate diagnosis in limited time, in the absence of specialists. It employs a graphical user interface and a fuzzy logic controller with rule viewer for identification of the type of peripheral neuropathy. An integrated medical records database is also developed for the storage and retrieval of the data. The system consists of 24 input fields, which includes the clinical values of the diagnostic test and the clinical symptoms. The output field is the disease diagnosis, whether it is Motor (Demyelinating/Axonopathy) neuropathy, sensory (Demyelinating/Axonopathy) neuropathy, mixed type or a normal case. The results obtained were compared with the expert's opinion and the system showed 93.27 % accuracy. The study aims at showing that Fuzzy Expert Systems may prove useful in providing diagnostic and predictive medical opinions. It enables the clinicians to arrive at a better diagnosis as it keeps the expert knowledge in an intelligent system to be used efficiently and effectively.
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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.