Artificial Intelligence in Medical Imaging

PART I: INTRODUCTION: Introduction: Game changers in radiology.- PART II: TECHNIQUES: The role of medical imaging computing, informatics and machine learning in healthcare.- History and evolution of A.I. in medical imaging.- Deep Learning and Neural Networks in imaging: basic principles.- PART III DEVELOPMENT of AI APPLICATIONS: Imaging biomarkers.- How to develop A.I. applications.- Validation of A.I. applications.- PART IV: BIG DATA IN RADIOLOGY: The value of enterprise imaging.- Data mining in radiology.- Image biobanks.- The quest for medical images and data.- Clearance of medical images and data.- Legal and ethical issues in AI.- PART V: CLINICAL USE OF A.I. IN RADIOLOGY: Pulmonary diseases.- Cardiac diseases.- Breast cancer.- Neurological diseases.- PART VI: IMPACT of A.I. on RADIOLOGY: Applications of A.I. beyond image analysis.- Value of structured reporting for A.I..- The role of A.I. for clinical trials.- Market and economy of A.I.: evolution.- The role of an A.I. ecosystem for radiology.- Advantages and risks of A.I. for radiologists.- Re-thinking radiology.

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• Radiologia
• Inteligência artificial

Artificial Intelligence in Medical Imaging;Deep Learning in Medical Imaging;Machine Learning in Medical Imaging;Techniques for AI in Medical Imaging;Big Data in Radiology;Artificial Intelligence in Radiology;Medical Imaging Informatics;Imaging Biomarkers;Medical Imaging Computing;Data Mining in Radiology;Image Biobanks