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Emerging Methods in Machine Learning and Deep Learning approaches for medical Imagics in Theranosis

Rakesh Sharma

Abstract


Medical imaging has emerged as a monitoring tool of theragnostic images using original medical images obtained from MRI-CT-PET as original information and predict the outcome of treatment.  Early information from images reduces the mortality due to cancer, tumors and dreadful diseases. Machine learning uses large data to have new predictive information while deep learning speculates all details based on previous a priori data information using a multilayered neural network of used datasets. The present study puts an evidence of using previous studies on ML and DL significantly helpful to classify multiple diseases based on imaging dataset evaluation in making accurate diagnosis and assess the treatment outcome in less time with high specificity and sensitivity. 

 


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