Application of Artificial Intelligence Techniques for Monkeypox: A Systematic Review

Abstract

Monkeypox or Mpox is an infectious virus predominantly found in Africa. It has spread to many countries since its latest outbreak. Symptoms such as headaches, chills, and fever are observed in humans. Lumps and rashes also appear on the skin (similar to smallpox, measles, and chickenpox). Many artificial intelligence (AI) models have been developed for accurate and early diagnosis. In this work, we systematically reviewed recent studies that used AI for mpox-related research. After a literature search, 34 studies fulfilling prespecified criteria were selected with the following subject categories: diagnostic testing of mpox, epidemiological modeling of mpox infection spread, drug and vaccine discovery, and media risk management. In the beginning, mpox detection using AI and various modalities was described. Other applications of ML and DL in mitigating mpox were categorized later. The various machine and deep learning algorithms used in the studies and their performance were discussed. We believe that a state-of-the-art review will be a valuable resource for researchers and data scientists in developing measures to counter the mpox virus and its spread.

Challenges in Clinical Diagnosis of Clade I Mpox: Highlighting the Need for Enhanced Diagnostic Approaches

“…By leveraging AI, we can aim to bridge the diagnostic gap, ensuring timely and accurate detection of Mpox, even in the most challenging environments, thereby improving patient outcomes and controlling the spread of the disease more effectively. (22, 23)…”

“…By leveraging AI, we can aim to bridge the diagnostic gap, ensuring timely and accurate detection of Mpox, even in the most challenging environments, thereby improving patient outcomes and controlling the spread of the disease more effectively. (22,23) Limitations This study included a relatively low number of participants, because few clinicians worldwide have current or recent experience managing patients with Clade I mpox. The response rate was also challenged by difficulty identifying and reaching clinicians who work in remote areas with limited internet connection.…”

Monkeypox Virus and Other Emerging Outbreaks: An Overview and Future Perspective

“…58 The use of artificial intelligence (AI) through various methods for the diagnosis of MPX is discussed in a systematic review conducted by Chadaga et al Although still a topic of further research, this automated diagnostic technique can eliminate misdiagnosis, reduce the time between PCR testing and beginning of treatment, and can be used in developing countries where there is a lack of medical facilities. 59 Although mass vaccination is not recommended, preexposure and post-exposure vaccination in high risk individuals prevents and reduces the severity of disease respectively. Only second and third generation vaccines can be used for this purpose.…”

Deep hybrid model for Mpox disease diagnosis from skin lesion images

“…However, research is insufficient in applying CAD 22 for primary diagnosis due to the limited availability of publicly accessible datasets for training and testing purposes. CNNs 23 have demonstrated remarkable ability in analyzing medical images and identifying patterns related to various diseases, making them promising candidates for MPox diagnosis. To address the lack of data and enhance the efficiency of DL models, researchers have widely adopted TL, which involves repurposing pre‐trained models trained on large datasets for similar tasks, leading to improved model performance.…”