About this Research Topic
In the context of infectious diseases, AI has been successfully used for detecting and tracking the progression of various infectious diseases, such as COVID-19, malaria and tuberculosis.
The contribution of AI to infectious diseases includes various aspects, the most common of which is the use of big data, machine learning or deep learning algorithms. These methods can be used to develop personalized prediction models to determine the risk and prognosis of a certain pathogen or the associated complications. Based on the individualized prognosis prediction model established for each patient, it can assist physicians in making clinical decisions in complex situations, and contribute to disease prevention and treatment, as well as joint decision-making between doctors and patients.
This Research Topic welcomes original research, reviews and case reports on the application of AI, Machine Learning or deep learning algorithms on (including but not limited to) the following themes:
• The diagnosis of infectious diseases
• The treatment of infectious diseases
• Progression of infectious disease in an individual.
• Transmission of infectious diseases between individuals and a population
• Clinical decision making for infectious diseases.
• Antimicrobial resistance
• Potential drug targets of pathogens.
Keywords: artificial intelligence, prevention, treatment, machine learning, medical decision-making, COVID-19, Tuberculosis, Malaria
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.