Abstract
Introduction: Amyotrophic lateral sclerosis (ALS) is a rare and fatal neurological disease that leads to progressive motor function degeneration. Diagnosing ALS is challenging due to the absence of a specific detection test. The use of artificial intelligence (AI) can assist in the investigation and treatment of ALS. Methods: We searched seven databases for literature on the application of AI in the early diagnosis and screening of ALS in humans. The findings were summarized using random-effects summary receiver operating characteristic curve. The risk of bias (RoB) analysis was carried out using QUADAS-2 or QUADAS-C tools. Results: In the 34 analyzed studies, a meta-prevalence of 47% for ALS was noted. For ALS detection, the pooled sensitivity of AI models was 94.3% (95% CI–63.2% to 99.4%) with a pooled specificity of 98.9% (95% CI–92.4% to 99.9%). For ALS classification, the pooled sensitivity of AI models was 90.9% (95% CI–86.5% to 93.9%) with a pooled specificity of 92.3% (95% CI–84.8% to 96.3%). Based on type of input for classification, the pooled sensitivity of AI models for gait, electromyography, and magnetic resonance signals was 91.2%, 92.6%, and 82.2%, respectively. The pooled specificity for gait, electromyography, and magnetic resonance signals was 94.1%, 96.5%, and 77.3%, respectively. Conclusions: Although AI can play a significant role in the screening and diagnosis of ALS due to its high sensitivities and specificities, concerns remain regarding quality of evidence reported in the literature.
Original language | English |
---|---|
Pages (from-to) | 425-436 |
Number of pages | 12 |
Journal | Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration |
Volume | 25 |
Issue number | 5-6 |
DOIs | |
Publication status | Published - 2024 |
Keywords*
- amyotrophic lateral sclerosis
- ALS
- artificial intelligence
- AI
- diagnostiics
- sensitivity
- specificity
Field of Science*
- 1.2 Computer and information sciences
- 3.2 Clinical medicine
Publication Type*
- 1.1. Scientific article indexed in Web of Science and/or Scopus database