Artificial Intelligence in Medical Imaging for Disease Diagnosis: A Comprehensive Review
DOI:
https://doi.org/10.70445/gjus.3.1.2026.49-76Keywords:
Artificial Intelligence, Medical Imaging, Disease diagnosis, Deep Learning, Machine learning, Image analysis, Cancer detectionAbstract
The integration of Artificial Intelligence (AI) into medical imaging has revolutionized how diseases are detected, diagnosed, and treated. Artificial Intelligence (AI) is reshaping medical imaging, enhancing disease detection, diagnosis, and medical decision-making. This review discusses the use of machine learning, deep learning, and sophisticated image-analysis methods for each of these modalities: X-ray, computed tomography, magnetic resonance imaging, ultrasound, and digital pathology. The potential of AI in cancer diagnosis, neurological diseases, cardiovascular diseases, and pulmonary diseases shows promise. Moreover, new trends like Explainable Artificial Intelligence, Multimodal Learning can facilitate personalized diagnosis. But problems with accuracy, algorithmic bias, interpretability, privacy and clinical validation exist. To fully leverage the potential of AI in medical imaging and enhance patient care, responsible implementation and ongoing research are crucial.
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