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Explores the foundations of AI technologies-machine learning, deep learning, computer vision, and natural language processing-tailored to diagnostic applications.
Highlights AI's transformative role in medical imaging, pathology, genomics, cardiology, and dermatology.
Examines case studies where AI tools enhance accuracy, efficiency, and early detection in clinical practice.
Discusses ethical, legal, and social implications of AI in healthcare, including data privacy, bias, and accountability.
Provides insights into the integration of AI into clinical workflows, regulatory frameworks, and medical training.
Highlights global perspectives, showing how AI-driven diagnostics are expanding healthcare access in low-resource settings.
Serves as a comprehensive guide for healthcare professionals, researchers, students, and policymakers navigating AI-enabled diagnostics.
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