Deep and Transfer Learning Approaches for Automated Early Detection of Monkeypox (Mpox) Alongside Other Similar Skin Lesions and Their Classification
Problem
Mpox symptoms resemble chickenpox and measles, causing possible misdiagnosis, and a rapid, automated early diagnosis method is needed.
Why it matters
Misdiagnosis of mpox delays isolation and treatment of a disease that has spread to more than 100 nonendemic countries.
What the AI did
The study proposes deep learning and transfer learning models for automated early mpox diagnosis from images, alongside classification of similar skin lesions.
Results
not stated in source
Impact
The abstract states model performances are discussed but the provided evidence cuts off before any numbers.
Record
| Venue | ACS Omega |
|---|---|
| Published | 2023 |
| Work type | article |
| Authors | Madhumita Pal, Ahmed Mahal, Ranjan K. Mohapatra, Ahmad J. Obaidullah, Rudra Narayan Sahoo, Gurudutta Pattnaik, Sovan Pattanaik, Snehasish Mishra et al. |
| Citations | 47 (OpenAlex, at import time) |
| References | 26 |
| Model or method | deep and transfer learning models (specific architectures not stated in source) |
| Organization | not stated in source |
| Primary source | https://doi.org/10.1021/acsomega.3c02784 |
| Open access | gold |
| Keywords | monkeypox, deep learning, transfer learning, skin lesion classification, early diagnosis, misdiagnosis |
Importance rating
major — millions of lives, an industry or a field
Abstract states mpox emerged as a global threat spread to more than 100 nonendemic countries, a public health emergency; misdiagnosis with chickenpox/measles delays care.