Paper Key : IRJ************143
Author: Saburi Polshettiwar,Vibha Raghwani,Nisha Jagtap,Shubhangi Gondage
Date Published: 05 Mar 2023
Monkeypox outbreaks have been detected in 75 countries so far, and they are rapidly expanding over the world. While the skin lesions and rashes of monkeypox frequently resemble those of other poxes, such as chickenpox and cowpox, their clinical characteristics match those of smallpox. Because of these similarities, it might be difficult for medical practitioners to diagnose monkeypox simply looking at the visual characteristics of lesions and rashes. Healthcare workers also lack expertise because monkeypox was uncommon prior to the current outbreak. The scientific community has expressed a growing interest in employing artificial intelligence (AI) to diagnose monkeypox from digital skin photos as a result of AI's success in COVID-19 identification. The bottleneck for employing AI in monkeypox detection, however, has been the scarcity of monkeypox skin picture data. The Monkeypox Skin Image Dataset 2022, the largest of its sort to date, was thus recently released. Also, in this research, we make use of this dataset to examine the viability of detecting monkeypox on skin photos using cutting-edge AI deep models. According to our work, deep AI models can identify monkeypox with an 85% accuracy rate from digital skin pictures. More training samples are needed to train those deep models in order to achieve a more robust detection power.
DOI LINK : 10.56726/IRJMETS34109
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