Efforts to reduce the burden of Tuberculosis (TB) are challenged by the persistent social inequalities in health, the limited number of local healthcare professionals, and the weak healthcare infrastructure found in resource-poor communities. Reducing the TB diagnosis delay is critical in mitigating disease transmission and minimizing the reproductive rate of the TB epidemic in high-burden areas. The main objective of this proposal is to expedite the TB diagnosis process by developing novel image processing and machine learning techniques to analyze chest X-ray images thus reducing patient wait times for being diagnosed with TB. The study will be conducted in the district of Carabayllo, a densely occupied, high-burden TB area in Lima, the capital of Per. Efforts to develop the proposed user-centered, mobile device-based computing system are aligned with the mission of the National Institute of Biomedical Imaging and Bioengineering (NIBIB) and its strategic goals 2 and 4 in particular-the proposed socio-technical intervention aims at developing biomedical imaging techniques (i.e. wireless and image sensing/analyzing) to enable a point-of-care mobile device-based computing system for TB screening and diagnostic. Anticipated outcomes include a) a large-scale, real-world, well-annotated, and public available chest X-ray image database for TB screening, b) development of new image analysis techniques for X-ray image capturing and pre- processing, and c) novel learning-based feature extraction and classification algorithms. This interdisciplinary effort, involving community, university, hospitals and health care establishments in all stages of the research, responds to the need for increased partnerships between academia and community stakeholders, and the potential for building capacity in biomedical and technology solutions for health in both directions (North-South, South-North). Its scientific contribution lies in the intersection of three NIBIB scientific program areas including image processing, telehealth, and biomedical informatics.
This project is highly relevant to public and global health because it offers a socio-technical solution for resource-poor communities severely affected by TB. Outcomes of this project will contribute significantly to improving specific healthcare processes affecting hard-to-reach communities that are socially excluded and lack the benefits of technological advances while broadening our understanding about effective human centered designs to improve healthcare systems with mobile computing technologies.
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