A study and analysis on diagnosis of melanoma cancer with deep learning: A case study

P. Yashashwini Reddy, C. Kishor Kumar Reddy, Natassia Thandiwe Sithole

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

The riskiest type of skin cancer is known as melanoma cancer, with more than millions of human popula¬tions identifying with this type in the last two decades around the world. Swift spreading nature to other areas of the body makes this type of cancer the most hazardous cancer among all other skin cancers. It can be reversed if identified at its primary stage, else chances of survival would be less if it is identi¬fied in its severe stage. There are several conventional methods to identify melanoma at primary stage performed by skin doctors, but there are a few limitations. To overcome the setbacks of conventional methods, artificial intelligence has been introduced to detect melanoma cancer. The application of con¬cepts of artificial intelligence (AI) made a good enhancement in the field of medicine. A deep learning algorithm termed CNN is highly opted in melanoma detection as it shows appropriate outcomes.

Original languageEnglish
Title of host publicationFederated Learning and AI for Healthcare 5.0
PublisherIGI Global
Pages203-218
Number of pages16
ISBN (Electronic)9798369310830
ISBN (Print)9798369310823
DOIs
Publication statusPublished - 18 Dec 2023

ASJC Scopus subject areas

  • General Medicine
  • General Health Professions
  • General Computer Science

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