Skin Disease Detection Through Deep Learning and Machine Learning

Skin Disease Detection Through Deep Learning and Machine Learning

Registration ID: IJNRD_220744

Published ID: IJNRD2405356

DOI: Click Here to Get

Vishal Gedam , Nikhil Bawane , Yash Sukhadeve , Sahil Ramteke , Tushar Bhogekar

Skin disease detection, deep learning, machine learning, image classification, dermatology, convolutional neural networks (CNN), feature extraction, dataset, medical imaging, computer-aided diagnosis, skin lesion segmentation, dermatoscopic images, predictive modeling, skin cancer detection.

Dermatological diseases are the most prevalent in the world. Despite its prevalence, diagnosis is extremely difficult and requires extensive field experience. We present a method for detecting various types of these diseases in this project. We used computer vision and machine learning to accurately identify diseases at two stages. The project's goal is to identify the type of skin disease and recommend the best treatment. In the first stage of the image, the skin disease is subjected to various types of preprocessing techniques, followed by feature extraction. In the second stage, machine learning algorithms are used to identify diseases based on skin analysis and observation. Deep learning techniques have emerged as promising tools for automating skin disease diagnosis in recent years. This study provides an in-depth examination of recent advances in skin disease detection using deep learning models.

Published Paper   E-Certificate

"Skin Disease Detection Through Deep Learning and Machine Learning", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 5, page no.d501-d507, May-2024, Available :https://ijnrd.org/papers/IJNRD2405356.pdf

Volume 9 Issue 5, May-2024

Pages : d501-d507

Paper Reg. ID: IJNRD_220744

Published Paper Id: IJNRD2405356

Downloads: 000121156

Research Area: Information Technology 

Country: Nagpur, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2405356.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2405356

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 8 | August 2025

IJNRD is Scholarly open access journals, Peer-reviewed, and Refereed Journals, High Impact factor 8.76 (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) with Open-Access Publications.

INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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Current Issue: Volume 10 | Issue 8

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