Keynote Speakers Computer-Based Systems for Aiding Global Health Challenges

Opportunistic HIV and TB co-infections are a dual epidemic resulting in significant mortality. According to the WHO, there are estimated to be over one million people worldwide who have the diseases, and the burden of disease is particularly high in sub-Saharan Africa and of growing concern in Asia. Meanwhile, levels of multi-drug resistant TB are increasing in several parts of the world. TB is a major cause of death among people living with HIV/AIDS, whose impaired immune systems make them particularly vulnerable. X-ray screening is an effective low-cost approach to improve diagnosis and management, but difficult to carry out in low-resource regions of the world. NIH researchers, led by Sameer Antani, Ph.D., have developed a system based on machine learning algorithms for the automated screening of digital chest X-ray images for pulmonary abnormalities with a special focus on TB. The system is being betatested on a mobile chest X-ray truck traveling through various sites in rural western Kenya. Collaborators on this project include Indiana University School of Medicine, AMPATH – a large HIV treatment program, and Moi Teaching and Referral Hospital in Kenya. Wide use of this system would potentially enable a significant time reduction in effort and time, from days to minutes, in human expert radiological diagnosis and provide critical decision support to field clinical officers for early appropriate treatment for the HIV positive population. The talk will describe elements of the system, the challenges in its design, the scientific advances, and also describe its impact. The talk will also briefly highlight a second project focusing on the malaria epidemic in parts of Asia and Africa, its treatment, and activities by NIH computational science researchers for developing systems to aid in medical research and clinical decision making.