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: 10319442
• 负责人: Peter Amoako-Yirenkyi
• 金额: $ 34.99万
• 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/10319442
• 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 - 加纳儿童健康数据科学 (DS-CHANGE) 培训项目 DS-CHANGE 培训计划的目标是培养夸梅·恩克鲁玛大学的数据科学能力 科学技术部 (KNUST) 并培养一支合格的数据科学家骨干队伍，专注于儿童健康 加纳。我们将通过跨学科的指导培训和体验式学习来培养这支科学家队伍 生物医学数据科学学科（应用数学、计算机科学、临床信息学、 生物统计学、流行病学）、健康状况（疟疾、损伤和先天性异常）和生物医学 领域（例如儿科、寄生虫学）。教师和研究生学员将解决计算问题 加纳复杂的儿童健康问题。我们的计划重点关注儿童死亡/残疾的十大原因中的 3 个 在加纳，包括疟疾、损伤和先天畸形（口面部裂）。我们的目标是： 目标 1：提供跨数据科学领域的综合指导跨学科培训计划 向不同的加纳研究生群体介绍方法、健康状况和生物医学领域 硕士和博士生。 目标 2：通过 (a) 促进提高 KNUST 在生物医学数据科学方面的师资和机构能力 数据科学方法的交叉培训； (b) 发展生物医学数据科学方面更深入的专业知识 方法; (c) 提高生物医学数据科学的教学和指导能力。 目标 3：提高教师和研究生学员对团队科学有效方法的熟练程度，以便 具有最少重叠专业知识的跨学科团队可以协同运作。 合作：该项目建立在 KNUST 和 KNUST 之间已建立的合作基础上 华盛顿大学 (UW)、西雅图儿童医院和研究所以及非营利性微笑列车。方法： KNUST 研究生学员将获得 KNUST 数据科学硕士或博士学位，该学位将得到支持 在西雅图进行为期 3 个月的实习，撰写了一篇关于现实世界加纳儿童健康问题的论文。国立科技大学师资队伍 学员将参加与威斯康星大学教师的教师交流。选择 KNUST 教师将完成 UW 数据科学领域的专业证书课程。所有学员将参加每月一次的 Zoom 研讨会 以提高跨学科的有效性。影响：我们将培训 13 名研究生学员和 16 名教职人员，以建立一个强大的团队 KNUST 生物医学数据科学研究生项目。学员将成功竞争研究经费， 将为儿童健康的证据基础做出贡献，并将担任数据科学和儿童领域的领导者 KNUST 和其他加纳机构的健康。