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Title: :  Skin Cancer or Skin Diseases Detection Using Machine Learning
PaperId: :  21925
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 9 Issue 6 2023
DUI:    16.0415/IJARIIE-21925
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
SUBHASH PATIL SKN SINHGAD INSTITUTE OF TECHNOLOGY AND SCIENCE -[SKNSITS]
PRAJAKTA KADU THORMISE SKN SINHGAD INSTITUTE OF TECHNOLOGY AND SCIENCE -[SKNSITS]
APEKSHA BALASAHEB ABHALE SKN SINHGAD INSTITUTE OF TECHNOLOGY AND SCIENCE -[SKNSITS]
RUTUJA BABASAHEB ROKADESKN SINHGAD INSTITUTE OF TECHNOLOGY AND SCIENCE -[SKNSITS]

Abstract

Computer Engineering
Medical imaging, skin cancer, melanoma classification, dermoscopy, deep learning, network fusion.
Skin cancer, a concerning public health predicament, with over 5,000,000 newly identified cases every year, just in the United States. Generally, skin cancer is of two types: melanoma and non-melanoma. Melanoma also called as Malignant Melanoma is the 19th most frequently occurring cancer in women and men. It is the deadliest form of skin cancer. In the year 2015, the global occurrence of melanoma was approximated to be over 350,000 cases, with around 60,000 deaths. The most prevalent non-melanoma tumors are squamous cell carcinoma and basal cell carcinoma. Non-melanoma skin cancer is the 5th most frequently occurring cancer, with over 1 million diagnoses worldwide in 2018. As of 2019, greater than 1.7Million new cases are expected to be diagnosed. Even though the mortality is significantly high, but when detected early, survival rate exceeds 95%. This Motivates us to come up with a solution to save millions of lives by early detection of skin cancer. Convolutional Neural Network (CNN) or ConvNet, are a class of deep neural networks, basically generalized version of multi-layer perceptron’s. CNNs have given highest accuracy in visual imaging tasks. This project aims to develop a skin cancer detection CNN model which can classify the skin cancer types and help in early detection. The CNN classification model will be developed in Python using Keras and Tensor Flow in the backend. The model is developed and tested with different network architectures by varying the type of layers used to train the network including but not limited to Convolutional layers, Dropout layers, pooling layers and dense layers. The model will also make use of Transfer Learning techniques for early convergence.

Citations

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IJARIIE SUBHASH PATIL , PRAJAKTA KADU THORMISE , APEKSHA BALASAHEB ABHALE , and RUTUJA BABASAHEB ROKADE. "Skin Cancer or Skin Diseases Detection Using Machine Learning" International Journal Of Advance Research And Innovative Ideas In Education Volume 9 Issue 6 2023 Page 146-151
MLA SUBHASH PATIL , PRAJAKTA KADU THORMISE , APEKSHA BALASAHEB ABHALE , and RUTUJA BABASAHEB ROKADE. "Skin Cancer or Skin Diseases Detection Using Machine Learning." International Journal Of Advance Research And Innovative Ideas In Education 9.6(2023) : 146-151.
APA SUBHASH PATIL , PRAJAKTA KADU THORMISE , APEKSHA BALASAHEB ABHALE , & RUTUJA BABASAHEB ROKADE. (2023). Skin Cancer or Skin Diseases Detection Using Machine Learning. International Journal Of Advance Research And Innovative Ideas In Education, 9(6), 146-151.
Chicago SUBHASH PATIL , PRAJAKTA KADU THORMISE , APEKSHA BALASAHEB ABHALE , and RUTUJA BABASAHEB ROKADE. "Skin Cancer or Skin Diseases Detection Using Machine Learning." International Journal Of Advance Research And Innovative Ideas In Education 9, no. 6 (2023) : 146-151.
Oxford SUBHASH PATIL , PRAJAKTA KADU THORMISE , APEKSHA BALASAHEB ABHALE , and RUTUJA BABASAHEB ROKADE. 'Skin Cancer or Skin Diseases Detection Using Machine Learning', International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 6, 2023, p. 146-151. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Skin_Cancer_or_Skin_Diseases_Detection_Using_Machine_Learning_ijariie21925.pdf (Accessed : ).
Harvard SUBHASH PATIL , PRAJAKTA KADU THORMISE , APEKSHA BALASAHEB ABHALE , and RUTUJA BABASAHEB ROKADE. (2023) 'Skin Cancer or Skin Diseases Detection Using Machine Learning', International Journal Of Advance Research And Innovative Ideas In Education, 9(6), pp. 146-151IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Skin_Cancer_or_Skin_Diseases_Detection_Using_Machine_Learning_ijariie21925.pdf (Accessed : )
IEEE SUBHASH PATIL , PRAJAKTA KADU THORMISE , APEKSHA BALASAHEB ABHALE , and RUTUJA BABASAHEB ROKADE, "Skin Cancer or Skin Diseases Detection Using Machine Learning," International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 6, pp. 146-151, Nov-Dec 2023. [Online]. Available: https://ijariie.com/AdminUploadPdf/Skin_Cancer_or_Skin_Diseases_Detection_Using_Machine_Learning_ijariie21925.pdf [Accessed : ].
Turabian SUBHASH PATIL , PRAJAKTA KADU THORMISE , APEKSHA BALASAHEB ABHALE , and RUTUJA BABASAHEB ROKADE. "Skin Cancer or Skin Diseases Detection Using Machine Learning." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 9 number 6 ().
Vancouver SUBHASH PATIL , PRAJAKTA KADU THORMISE , APEKSHA BALASAHEB ABHALE , and RUTUJA BABASAHEB ROKADE. Skin Cancer or Skin Diseases Detection Using Machine Learning. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2023 [Cited : ]; 9(6) : 146-151. Available from: https://ijariie.com/AdminUploadPdf/Skin_Cancer_or_Skin_Diseases_Detection_Using_Machine_Learning_ijariie21925.pdf
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