Artificial Intelligence Techniques in Clinical Decision Support Systems in Radiology Using X-ray and MRI

Abstract: Artificial Intelligence (AI) is changing the Clinical Decision Support Systems (CDSS) in radiology, especially in X-ray and Magnetic Resonance Imaging (MRI). This study involves a qualitative systematic synthesis of 70 relevant publications with PRISMA approach to assess AI approaches, clinical applications and real-world deployment in radiological CDSS. The findings show that deep learning models like CNNs, 3D CNNs, U-Net, transformer-based models dominate in today's applications. The advantage of AI-CDSS based on X-rays are for screening and classification, whilst AI-CDSS based on MRI are better for volumetric analysis, tumour segmentation, and data monitoring. Aidoc, Viz.ai, Qure.ai, Arterys and DeepMind Health demonstrate the therapeutic use of AI in triage, anomaly detection and workflow optimisation. However, challenges remain concerning interpretability, data heterogeneity, generalisability and clinical integration. AI is rapidly evolving as a vital companion in radiological CDSS, improving accuracy and efficiency.

Keywords: Artificial Intelligence, Clinical Decision Support Systems, Radiology, X-ray, MRI, Deep Learning, Explainable AI