Diagnostic performance of artificial intelligence in multiple sclerosis: a systematic review and meta-analysis.
Fardin NabizadehElham RamezannezhadAmirhosein KargarAmir Mohammad SharafiAli GhaderiPublished in: Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology (2022)
Overall, AI models can further improve our diagnostic practice in MS patients. Our results indicate that the use of AI can aid the clinicians in accurate diagnosis of MS and improve current diagnostic approaches as most of the parameters including accuracy, sensitivity, specificity, precision, and AUC were considerably high, especially when using MRI data.
Keyphrases
- artificial intelligence
- multiple sclerosis
- big data
- machine learning
- deep learning
- end stage renal disease
- mass spectrometry
- ejection fraction
- newly diagnosed
- chronic kidney disease
- primary care
- healthcare
- magnetic resonance imaging
- palliative care
- prognostic factors
- high resolution
- electronic health record
- contrast enhanced
- computed tomography
- magnetic resonance