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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Issue: August 2022

Volume 7 | Issue 8

Impact factor: 8.15

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Paper Title: A Deep Learning Approach In Skin Cancer Prediction
Authors Name: Aditi V. Motekar , Dolly A. Soni , Radhika K. Sharma , Saumya R. Agrawal , Priyanka V. Deshmukh
Unique Id: IJSDR2106009
Published In: Volume 6 Issue 6, June-2021
Abstract: Skin cancer is an alarming disease for mankind. The necessity of early diagnosis of the skin cancer has been increased because of the rapid growth rate of Melanoma skin cancer, its high treatment costs, and death rate. Melanoma, also known as malignant melanoma, is a type of cancer that develops from the pigment-containing cells known as melanocytes. Melanoma accounts for approximately 75% of deaths associated with skin cancer. Melanomas typically occur in the skin but may rarely occur in the mouth, intestines, or eye. In women they most commonly occur on the legs, while in men they are most common on the back. Due to the costs for dermatologists to examine every patient, there arises a need for an automated system to assess a patient's risk of melanoma using images of their skin lesions captured using a standard digital camera. In the proposed method the image is processed, segmented and features are extracted. Then the features are compared with the given database and classification is done using artificial neural network. This cancer cells are detected manually and it takes time to cure in most of the cases. This project proposes an artificial skin cancer detection system using deep learning method. The features of the affected skin cells are extracted after the segmentation of the dermoscopic images using feature extraction technique. A deep learning-based method convolutional neural network classifier is used for the stratification of the extracted features.
Cite Article: "A Deep Learning Approach In Skin Cancer Prediction", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.6, Issue 6, page no.63 - 67, June-2021, Available :http://www.ijsdr.org/papers/IJSDR2106009.pdf
Downloads: 000101746
Publication Details: Published Paper ID: IJSDR2106009
Registration ID:193387
Published In: Volume 6 Issue 6, June-2021
DOI (Digital Object Identifier):
Page No: 63 - 67
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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