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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM29479

Human Skin Disease Detection using Machine Learning

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM29479

Volume:

8 |

3 |

Mar 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

PSS

Prof. Swati Salunkhe

NT

Nikita Takne

MT

Mugdha Tadwalkar

YT

Yash Tambat

PV

Pushkar Visave

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Abstract

Due to its intricacy, dermatology is one of the most unpredictable and challenging fields to diagnose. To determine the skin condition a patient may be experiencing; numerous testings are frequently required in the field of dermatology. Depending on the practitioner, the duration could change. This is also based on their personal experience. Therefore, a system that can diagnose skin diseases without any of these limitations is needed. We suggest an automated image-based method that uses machine learning classification to identify skin disorders. Based on numerous aspects of the photographs, this system will use computational technique to analyze, process, and relabel the image data. Images of the skin are filtered to remove undesirable

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Cite This Article

Prof. Swati Salunkhe, Nikita Takne, Mugdha Tadwalkar, Yash Tambat, Pushkar Visave, "Human Skin Disease Detection using Machine Learning," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 3, Mar 2024.

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12/31/45372

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Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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