A systematic review and meta-analysis on the diagnostic accuracy of artificial intelligence and computer-aided diagnosis of lumbar prolapsed intervertebral disc - Sandeep Pattnaik; Manu Goyal; Rajneesh Kumar Gujral; Amit Mittal (Neuroscience Informatics)
Introduction: Lumbar prolapsed intervertebral disc (PIVD) is a debilitating lower back condition, whose accurate and timely diagnosis is crucial for its effective management. Artificial intelligence (AI) and computer-aided diagnosis (CAD) techniques have the potential to revolutionise diagnosis by improving accuracy, efficiency, and objectivity. This systematic review with meta-analysis thus aims to thoroughly assess the available knowledge on the usability of different AI and CAD-based tools in lumbar PIVD diagnosis. Methods: A systematic search of electronic databases, between June and August 2024 for relevant full-text studies. The primary outcomes for review included the diagnostic accuracy (of each AI and CAD system. Subsequently, a meta-analysis was conducted to synthesise the results of the included studies. Result: A total of eight studies were identified, evaluating thirteen CAD or AI systems. The meta-analysis involved three of the studies, and it demonstrated a high pooled sensitivity (0.901, 95% CI: 0.871–0.924) and specificity (0.919, 95% CI: 0.898–0.936) for lumbar PIVD diagnosis. Conclusion: To conclude, these findings strongly support the potential of AI/CAD systems to improve the accuracy and efficiency of lumbar PIVD diagnosis. Prospero ID: CRD42023444785