Understanding the key concepts of AI and deep learning . Describe emerging applications of deep learning techniques in radiology for lesion classification, detection, and segmentation. Current Applications and Future Impact of Machine Learning in Radiology.

Artificial intelligence is expected to play a huge role in transforming radiology practice. Therefore, we aim to provide a explanation on the very basics of artificial intelligence. Buzzwords of AL/ML/DL.[1] Introduction to deep learning in radiology : A- How does machine learning works? B-The difference between machine learning and Deep learning: C- The architecture of deep learning models : we introduce the artificial neural network in general and one specific type: the convolutional neural network. C-The learning process of CNN More sources are needed to...

Applications of deep learning in radiology I-Classification Classification with deep learning usually utilizes target lesions depicted in medical images, and these lesions are classified into two or more classes. For example, deep learning is frequently used for the classification of lung nodules on computed tomography (CT) images as benign or malignant (Fig. 13a). It is necessary to prepare a large number of training data with corresponding labels for efficient classification using CNN. For lung nodule classification, CT images of lung nodules and their labels (i.e.,...

Machine learning is likely to significantlly impact radiology in the future, by enhancing efficency , quaityt ,and precison of imagery . However , several important questions remain, Like : how will other stakeholders in the ecosystem respond? And will consumers ever learn to trust an algorithm, even one backed to rigorous studies?

H. M. Abdel Hafeez; Cairo/EG - nothing to disclose Hend Mohamed AbdelHafeez Ahmed Qualifications: M.B.B.C.H Faculty of Medicine, Cairo University , 2010 ( with distinction) M.SC (Master degree of Radio diagnosis ,2016. Azhar University, Cairo , Egypt ). ongoing doctorate degree of diagnostic radiology . Affiliations: Member of ESR(Egyptian society of Radiology ),ESOR,ESHI,ESOI,RSNA Present occupation Diagnostic radiology specialist . Contact information: [email protected]

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