Data Science for Child Health Now in Ghana (DS-CHANGE)

加纳现在的儿童健康数据科学 (DS-CHANGE)

• 批准号: 10490300
• 负责人: Peter Amoako-Yirenkyi
• 金额: $ 34.98万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-22 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10490300
• 关键词: Active Learning; Biometry; Cessation of life; Child; Child Health; Clinical Informatics; Collaborations; Complex; Congenital Abnormality; Data Science; Data Scientist; Discipline; Doctor of Philosophy; Educational process of instructing; Effectiveness; Epidemiology; Faculty; Funding; Ghana; Goals; Health; Injury; Institution; Malaria; Mathematics; Mentors; Methodology; Methods; Parasitology; Pediatric Hospitals; Pediatrics; Positioning Attribute; Research; Research Institute; Science; Scientist; Smiling; Technology; Training; Training Programs; Universities; Washington; biomedical data science; certificate program; computer science; congenital anomaly; disability; evidence base; externship; graduate student; institutional capacity; orofacial cleft; programs

PROGRAM ABSTRACT - Data Science for Child Health Now in Ghana (DS-CHANGE) Training Program Our goal for the DS-CHANGE Training Program is to build data science capacity at Kwame Nkrumah University of Science and Technology (KNUST) and develop a cadre of qualified data scientists focused on child health in Ghana. We will develop this cadre of scientists with mentored training and experiential learning that cross-sect biomedical data science disciplines (applied mathematics, computer science, clinical informatics, biostatistics, epidemiology), health conditions (malaria, injury and congenital anomalies), and biomedical domains (e.g. pediatrics, parasitology). Faculty and graduate student trainees will tackle computationally complex child health problems in Ghana. Our program focuses on 3 of the top 10 causes of child death/disability in Ghana including malaria, injury, and congenital malformations (orofacial clefts). We aim to: Aim 1: Deliver a comprehensive mentored interdisciplinary training program that cross-sects data science methodologies, health conditions, and biomedical domains to a diverse group of Ghanaian graduate-level MS and PhD trainees. Aim 2: Increase KNUST faculty and institutional capacity in biomedical data science by (a) facilitating cross-training in data science methodologies; (b) developing deeper expertise in biomedical data science methods; and (c) building teaching and mentoring proficiency in biomedical data science. Aim 3: Develop proficiency of faculty and graduate trainees in effective methods of team science so that interdisciplinary teams with minimal overlapping expertise can function synergistically. Collaboration: This program builds on established collaborations between KNUST and the University of Washington (UW), Seattle Children's Hospital and Research Institute, and the non-profit Smile Train. Approach: KNUST graduate trainees will obtain a Master or PhD degree in data science from KNUST that will be bolstered by a 3 month externship in Seattle with a thesis on a real world Ghana child health problem. KNUST faculty trainees will participate in faculty exchanges with UW faculty. Select KNUST faculty will complete a UW Professional Certificate Program in a data science domain. All trainees will participate in a monthly Zoom seminar to enhance interdisciplinary effectiveness. Impact: We will train 13 graduate trainees and 16 faculty for a robust biomedical data science graduate program at KNUST. Trainees will compete successfully for research funding, will contribute to the evidence base in child health, and will take up positions as leaders in data science and child health at KNUST and other Ghanaian institutions.

项目摘要-数据科学儿童健康现在在加纳（DS-CHANGE）培训计划