The AI/RHEUM knowledge-based computer consultant system in rheumatology. Performance in the diagnosis of 59 connective tissue disease patients from Japan
| Autor: | James F. Porter, Lawrence C. , Kingsland Iii, Donald A. B. Lindberg, Indravadan Shah, James M. Benge, Susan E. Hazelwood, Donald R. Kay, Mitsuo Homma, Masashi Akizuki, Makoto Takano, Gordon C. Sharp |
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| Rok vydání: | 1988 |
| Předmět: |
Male
medicine.medical_specialty Pathology Immunology Connective tissue Diagnostic accuracy Disease Diagnosis Differential Rheumatology Japan Artificial Intelligence Internal medicine medicine Immunology and Allergy Humans Lupus Erythematosus Systemic Pharmacology (medical) Diagnosis Computer-Assisted Medical diagnosis Connective Tissue Diseases Rheum business.industry Middle Aged medicine.disease Connective tissue disease medicine.anatomical_structure business Software |
| Zdroj: | Arthritis and rheumatism. 31(2) |
| ISSN: | 0004-3591 |
| Popis: | AI/RHEUM is a knowledge-based computer consultant system for the diagnosis of rheumatic diseases. Its diagnostic accuracy was evaluated using information that was supplied by Japanese rheumatologists on 59 patients with connective tissue diseases. The diagnoses of the AI/RHEUM model were in full or partial agreement with those of the Japanese rheumatologists in 54 of 59 cases (92%). Preliminary evaluation of the criteria tissue disease showed a sensitivity of 90% and a specificity of 96%. |
| Databáze: | OpenAIRE |
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