 |
International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
|
Issue: March 2026
Volume 11 | Issue 3
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21604
Article Published : 8531
Total Authors : 22438
Total Reviewer : 805
Total Countries : 159
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | Skin Cancer Detection Through Image Analysis And Machine Learning Technique |
| Authors Name: | Vikrant Pawar , Jay Rupareliya , Shrikant Bhise , Prof. Sunita Naik |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_200957
|
| Published Paper Id: | IJRTI2503194 |
| Published In: | Volume 10 Issue 3, March-2025 |
| DOI: | |
| Abstract: | This Skin cancer remains a significant global health concern, with rising cases attributed to prolonged ultraviolet (UV) radiation exposure, environmental changes, and lifestyle factors. Early detection is essential for improving survival rates and treatment effectiveness. This study presents an AI-driven approach for automated skin cancer detection using the VGG16 deep learning model, which analyzes dermoscopic images to classify skin lesions as benign or malignant. The proposed system follows a structured pipeline, beginning with image acquisition and preprocessing to enhance clarity and standardize input data. The VGG16 model, pre-trained on large image datasets, extracts deep features from skin lesion images, leveraging its hierarchical learning capabilities to identify patterns associated with malignancy. The classification process assigns probability scores, aiding in risk assessment and early intervention.To evaluate performance, the model was trained and tested on a publicly available dataset, with accuracy, sensitivity, and specificity as key evaluation metrics. Results demonstrate that VGG16 achieves high classification accuracy, making it a reliable tool for assisting healthcare professionals in preliminary screenings. The study also discusses challenges such as dataset biases, real-world generalization, and clinical integration, emphasizing the need for further optimization. By enhancing diagnostic precision and accessibility, this research contributes to the development of AI-powered tools for early skin cancer detection, supporting both medical practitioners and individuals seeking timely assessments. |
| Keywords: | AI in dermatology, Deep learning, Medical image analysis, Skin cancer detection, VGG16. |
| Cite Article: | "Skin Cancer Detection Through Image Analysis And Machine Learning Technique", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 3, page no.b627-b635, March-2025, Available :http://www.ijrti.org/papers/IJRTI2503194.pdf |
| Downloads: | 000457 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID: IJRTI2503194
Registration ID:200957
Published In: Volume 10 Issue 3, March-2025
DOI (Digital Object Identifier):
Page No: b627-b635 Country: Palghar, Maharashtra, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2503194 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2503194 |
| Share Article: | |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijrti.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
| Providing A digital object identifier by DOI.ONE How to Get DOI? |
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Join RMS/Earn 300
WhatsApp
Click Here
Click Here
Indexing Partner |
|||
| Copyright © 2026 - All Rights Reserved - IJRTI | |||