SCH: INT A.Soclotechnilcal Systems Systems Approach for Improving Tuberculosis Diagnostics Using Mobile Health Technologies

SCH：INT A.Soclotechnilcal Systems 使用移动医疗技术改进结核病诊断的系统方法

• 批准号: 9150601
• 负责人: Maria Julia Brunette
• 金额: $ 32.66万
• 依托单位: UNIVERSITY OF MASSACHUSETTS LOWELL
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-30 至 2020-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9150601
• 关键词: Academia; Address; Affect; Algorithms; Area; Benchmarking; Biomedical Technology; Capital; Cessation of life; Chest; Chronic Disease; Cities; Classification; Clinic; Communicable Diseases; Communities; Community Health; Complex; Computer Assisted; Computer Systems; Computer software; Computers; Data; Data Analytics; Databases; Development; Diagnosis; Diagnostic; Diagnostic radiologic examination; Discipline; Engineering; Epidemic; Evaluation; Female; Goals; Health; Health Professional; Health Sciences; Health Technology; Healthcare; Healthcare Systems; Hispanics; Human; Image; Image Analysis; Image Enhancement; Imaging Techniques; Intervention; Learning; Lung nodule; Machine Learning; Medical; Minority; Mission; National Institute of Biomedical Imaging and Bioengineering; Outcome; Patients; Peru; Process; Public Health; Reader; Recruitment Activity; Reporting; Research; Research Infrastructure; Resources; Running; Sensitivity and Specificity; Software Tools; System; Systems Analysis; Techniques; Technology; Testing; Thoracic Radiography; Time; Training; Treatment Protocols; Tuberculosis; Underrepresented Students; University Hospitals; Vaccines; Wireless Technology; Woman; World Health Organization; accurate diagnosis; base; bioimaging; biomedical informatics; clinical practice; compliance behavior; data exchange; design; digital imaging; disadvantaged population; disease transmission; global health; handheld mobile device; image processing; improved; mHealth; mobile computing; novel; open source; point of care; programs; public health relevance; reproductive; screening; social; social inequality; telehealth; tool

 DESCRIPTION (provided by applicant): 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 Perú. 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.

 描述（由适用提供）：减少结核病燃烧（TB）的努力受到健康的持续社会不平等，有限的当地医疗保健专业人员以及资源贫乏社区中发现的薄弱医疗保健基础设施的挑战。减少结核病诊断延迟对于减轻疾病传播并最大程度地减少高负荷地区结核病流行的生殖率至关重要。该提案的主要目的是通过开发新颖的图像处理和机器学习技术来分析胸部X射线图像，从而减少患者的等待时间，从而加快结核病诊断过程。该研究将在佩鲁首都利马的一个贫穷，高负责人的结核病区域卡拉巴伊洛（Carabayllo）区进行。开发提出的以用户为中心的基于移动设备的计算系统的努力与国家生物医学成像和生物工程研究所的使命（NIBIB）及其战略目标2和4（特别是拟议的社会技术干预旨在开发生物医学成像技术）（即无线电系统），并启用了启用移动式的coint-cace careming care and-care cace cace care and obios care and obios care and oby care care，诊断。预期的结果包括a）用于结核病筛选的大规模，现实世界，通知和公共可用的胸部X射线图像数据库，b）开发用于X射线图像捕获和预处理的新图像分析技术，以及c）新的基于学习的特征提取和分类算法。在研究的各个阶段涉及社区，大学，医院和医疗保健机构的这项跨学科工作，响应了学术界与社区利益相关者之间增加合作伙伴关系的需求，以及在两个方向（南北北部，南 - 北部）建立生物医学和技术解决方案的潜力。它的科学贡献在于三个尼比布科学计划领域的交集，包括图像处理，远程医疗和生物医学信息。