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Detection of Malignant Melanoma with Supervised Learning:A Review


Affiliations
1 RCEW, India
2 RCEW, CSE Department, India
     

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Malignant melanoma is increasing in some countries especially in Australia. Computational systems have been proposed for automatic diagnosis of skin cancer in order to aid dermatologist in early assessment of such disease. Several ways for image analysis targeted on dermoscopy imagery are projected for CAD system. To assist dermatologists in their diagnosis is the main aim of such system at an effective automated diagnosis. Malignant Melanoma needs to be diagnosed at their early stage, when the patient has a higher probability of cure.

Malignant melanoma is a kind of skin cancer whose severity even leads to death. For decreasing the chances of death earlier detection of Melanoma is necessary and the clinicians can treat the patients to increase the chances of survival. For detection of Melanoma using its features there are some machine learning algorithms are developed. This paper presents the review of Malignant Melanoma with supervised learning.


Keywords

Malignant Melanoma, Supervised Learning.
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  • Detection of Malignant Melanoma with Supervised Learning:A Review

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Authors

Neena Agrawal
RCEW, India
Vineet Khanna
RCEW, CSE Department, India

Abstract


Malignant melanoma is increasing in some countries especially in Australia. Computational systems have been proposed for automatic diagnosis of skin cancer in order to aid dermatologist in early assessment of such disease. Several ways for image analysis targeted on dermoscopy imagery are projected for CAD system. To assist dermatologists in their diagnosis is the main aim of such system at an effective automated diagnosis. Malignant Melanoma needs to be diagnosed at their early stage, when the patient has a higher probability of cure.

Malignant melanoma is a kind of skin cancer whose severity even leads to death. For decreasing the chances of death earlier detection of Melanoma is necessary and the clinicians can treat the patients to increase the chances of survival. For detection of Melanoma using its features there are some machine learning algorithms are developed. This paper presents the review of Malignant Melanoma with supervised learning.


Keywords


Malignant Melanoma, Supervised Learning.

References