Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

biochemistry, genetics and molecular biology

Artificial intelligence (AI) in Monkeypox infection prevention

Journal of Biomolecular Structure and Dynamics, Volume 41, No. 17, Year 2023

Monkeypox is a possible public health concern that requires appropriate attention in order to prevent the spread of the disease. Currently, artificial intelligence (AI) is making a significant impact on precision medicine, reshaping and integrating the large amount of data derived from multiomics analyses and revolutionizing the deep-learning strategies. There has been a significant progress in the use of AI to detect, screen, diagnose, and classify diseases, characterize virus genomes, assess biomarkers for prognostic and predictive purposes, and develop follow-up strategies. Hence, it is possible to use AI for the identification of disease clusters, cases monitoring, forecasting the future outbreak, determining mortality risk, diagnosing, managing, and identifying patterns for studying disease trends. AI may also be utilized to assist gene therapy and other therapies that we are not currently able to use in healthcare. It is possible to combine pharmacology and gene therapy with regenerative medicine with the help of AI. It will directly benefit the public in overcoming fear and panic of health risks. Therefore, AI can be an effective weapon to fight against Monkeypox infection, and may prove to be an invaluable future tool in improving the clinical management of patients. Key Points: Emergence and spread of the Monkeypox virus is a new public health crisis; threatening the world. This opinion piece highlights the urgently required information for immediate delivery of solutions on controlling and monitoring the spread of Monkeypox infection through Artificial Intelligence Communicated by Ramaswamy H. Sarma.
Statistics
Citations: 18
Authors: 3
Affiliations: 3
Identifiers
Research Areas
Genetics And Genomics
Health System And Policy
Infectious Diseases
Study Design
Cohort Study