Machine Learning in Medical Imaging for Early Detection of Skin Diseases
Upma Yadav1, Ashok Kumar2, Anamika Tiwari3, Saurabh Mukherjee4
1Ms Upma Yadav*, Department of CS & Eng. Bhabha Institute of Technology Kanpur Dehat, India.
2Mr Ashok Kumar, Department of CS Banasthali Vidyapith Rajasthan, India.
3Miss. Anamika Tiwari, Department of CS & Eng. Bhabha Institute of Technology Kanpur Dehat, India.
4Dr Saurabh Mukherjee, Department of CS Banasthali Vidyapith , Rajasthan, India.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 25, 2020. | Manuscript published on April 10, 2020. | PP: 513-516 | Volume-9 Issue-6, April 2020. | Retrieval Number: E3019039520/2020©BEIESP | DOI: 10.35940/ijitee.E3019.049620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Dermatology is a medical field that treats skin health and diseases. These skin diseases are perilous and often transmittable but can be cured or reversed with higher degree if detected at an early stage. Early detection and treatment can correct most skin disorders. Diagnosis of these diseases requires a sophisticated of proficiency due to the variety of their illustration aspects. As manual conclusion are often skewed and hardly reproducible, to achieve a more intent and undependable diagnosis, a computer aided diagnostic system should be considered. This work is to provide a comparative view of advancements the works as a robust literature of with techniques, methodology, experimented results and dataset done in medical science using medical images to predict diseases with early detection and higher accuracy .
Keywords: Dermatoscopic, Imaging Modality, Feature Map, Superficial learning, Shallow Learning, Deep Learning, Transfer Learning.
Scope of the Article: Deep learning