Medical AI has established itself as a robust and fruitful field in the last 30 years. Most resource poor countries face the triple burden of malaria, tuberculosis and HIV. This coupled with the problems of lack of infrastructure, scarcity of clinical staff, and complex clinical guidelines, have encouraged the application of AI in healthcare specifially on practical issues of field medical data collection, mining, and better integration with healthcare workfow. One such application is an HIV/AIDS antiretroviral therapy management system that uses AI algorithm to predict drug resistance and the progression of the disease. Another serious problem is the scarcity of personnel with sucient AI knowledge in the medical field. A distance education has shown its potential to remedy the problem.
@{15,
author = {Milan Hajek and Y. Singh},
title = {Medical AI - HIV/AIDS Treatment Management System},
abstract = {Medical AI has established itself as a robust and fruitful field in the last 30 years. Most resource poor countries face the triple burden of malaria, tuberculosis and HIV. This coupled with the problems of lack of infrastructure, scarcity of clinical staff, and complex clinical guidelines, have encouraged the application of AI in healthcare specifially on practical issues of field medical data collection, mining, and better integration with healthcare workfow. One such application is an HIV/AIDS antiretroviral therapy management system that uses AI algorithm to predict drug resistance and the progression of the disease. Another serious problem is the scarcity of personnel with sucient AI knowledge in the medical field. A distance education has shown its potential to remedy the problem.},
year = {2011},
journal = {Beyond AI: Interdisciplinary Aspects of Artificial Intelligence},
}
