Developments in Deep Learning for the Diagnosis of Skin Cancer

Dr Aziz Makandar and Mrs Ayisha Soudagar
Additional contact information
Dr Aziz Makandar: Professor, Department of Computer Science, Karnataka State Akkamahadevi Women’s University,Vijayapura-586101
Mrs Ayisha Soudagar: Research Scholar, Department of Computer Science, Karnataka State Akkamahadevi Women’s University,Vijayapura-586101

International Journal of Latest Technology in Engineering, Management & Applied Science, 2025, vol. 14, issue 6, 915-922

Abstract: The most prevalent kind of cancer worldwide is skin cancer. Early detection is crucial since failure to discover it in the primary stage could be fatal. Even though there are distinctions within the class and a lot of parallels between classes, it is too hard to tell with the naked eye. Due of the disease's widespread occurrence, several automated deep learning-based algorithms have been developed to date to assist physicians in spotting skin lesions early on. We trained VGG19 on the HAM10000 dataset by fine-tuning the Convolutional Neural Networks (CNNs) and using pre-trained ImageNet weights. With FT, the best performance was noted. With an overall accuracy of 82.4±1.9 percent, the developed model outperformed the one employed in transfer learning. This performance could save morbidity and treatment costs by providing a second opinion and bolstering the clinician's

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.ijltemas.in/DigitalLibrary/Vol.14Issue6/915-922.pdf (application/pdf)
https://www.ijltemas.in/papers/volume-14-issue-6/915-922.html (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bjb:journl:v:14:y:2025:i:6:p:915-922

Access Statistics for this article

International Journal of Latest Technology in Engineering, Management & Applied Science is currently edited by Dr. Pawan Verma

More articles in International Journal of Latest Technology in Engineering, Management & Applied Science from International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS)
Bibliographic data for series maintained by Dr. Pawan Verma ().