The Use of Artificial Intelligence in the Evaluation of Knee Pathology
| Autor: | George J. Watts, Elisabeth R. Garwood, Ganesh Joshi, Ryan Tai |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Pathology
medicine.medical_specialty Knee Joint Radiography Osteoarthritis Knee Injuries 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Artificial Intelligence Image Interpretation Computer-Assisted medicine Humans Radiology Nuclear Medicine and imaging Orthopedics and Sports Medicine Tendon healing 030203 arthritis & rheumatology medicine.diagnostic_test business.industry Magnetic resonance imaging Osteoarthritis Knee medicine.disease Magnetic Resonance Imaging Review article medicine.anatomical_structure Ligament Tears Artificial intelligence Applications of artificial intelligence business Cartilage Diseases |
| Zdroj: | Seminars in musculoskeletal radiology. 24(1) |
| ISSN: | 1098-898X |
| Popis: | Artificial intelligence (AI) holds the potential to revolutionize the field of radiology by increasing the efficiency and accuracy of both interpretive and noninterpretive tasks. We have only just begun to explore AI applications in the diagnostic evaluation of knee pathology. Experimental algorithms have already been developed that can assess the severity of knee osteoarthritis from radiographs, detect and classify cartilage lesions, meniscal tears, and ligament tears on magnetic resonance imaging, provide automatic quantitative assessment of tendon healing, detect fractures on radiographs, and predict those at highest risk for recurrent bone tumors. This article reviews and summarizes the most current literature. |
| Databáze: | OpenAIRE |
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