Medical Imaging Using Deep Learning

Abstract

The healthcare sector has been transformed by deep learning, a kind of artificial intelligence Convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are two examples of deep learning techniques that have been used to evaluate medical pictures, forecast illness outcomes, and enhance patient care. This study examines the important strides made by deep learning in the fields of radiology, pathology, genomics, and electronic health records (EHRs). Additionally, it draws attention to the difficulties and moral issues that come with the application of deep learning in healthcare, highlighting the necessity of strong data protection and model interpretability. Deep learning's potential and promising results in healthcare highlight its revolutionary effects on patient care, diagnosis, and treatment, ultimately raising the standard of care.