SyMPox: An Automated Monkeypox Detection System Based on Symptoms Using XGBoost

Alireza Farzipour, Roya Elmi, Hamid Nasiri
10/2/2023
cs.LGcs.AIcs.CY

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Abstract

Monkeypox is a zoonotic disease. About 87000 cases of monkeypox were confirmed by the World Health Organization until 10th June 2023. The most prevalent methods for identifying this disease are image-based recognition techniques. Still, they are not too fast and could only be available to a few individuals. This study presents an independent application named SyMPox, developed to diagnose Monkeypox cases based on symptoms. SyMPox utilizes the robust XGBoost algorithm to analyze symptom patterns and provide accurate assessments. Developed using the Gradio framework, SyMPox offers a user-friendly platform for individuals to assess their symptoms and obtain reliable Monkeypox diagnoses.

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Cite this paper

@article{farzipour2023sympox,
  title  = {SyMPox: An Automated Monkeypox Detection System Based on Symptoms Using XGBoost},
  author = {Alireza Farzipour and Roya Elmi and Hamid Nasiri},
  year   = {2023},
  eprint = {2310.19801},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2310.19801v1}
}

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