Data Science Training Core Pilot Programs

Assess, develop, and implement data science training curriculum

Click Here to See DSTC Program Participants

The AIM-AHEAD Training Practicum Pilot Program (PRIME) is coordinated by the Medstar Health Research Institute (MHRI), one of the DSTC participating institutions. The aim of PRIME is to support hands-on training experiences, as PRIME focuses on supporting training activities that may complement ongoing training and education occurring at the applicant’s institution. The PRIME learning objectives include: (1) Train the workforce in AI/ML using existing and/or synthetic datasets through the lens of health equity; (2) Increase knowledge, awareness at both local- and national-scale community engagement and empowerment in AI/ML; (3) Build community capacity and infrastructure in AI/ML to address community-centric health disparities and minority health. Potential training topics for PRIME fellows could include, but are not limited to: Trustworthiness, fairness, and ethical models around AI/ML solutions; Identifying and reducing bias in AI/ML; Cultural, Ethical, Political, and other societal impacts of AI/ML; Innovative AI/ML in Big Data solutions; Personalized/custom healthcare models; Applications of AI/ML/NLP in Imaging and telehealth.

 

PRIME Curriculum Overview:

  • Live Sessions
    • AWS Service Workbench
    • All of Us Data Browser
    • BioData Catalyst
    • N3C
  • Asynchronous courses
  • Projects
    • Group poster project
    • Individual final report

The DSTC Curriculum Development Pilot Program is focused on enhancing curricula by providing grant awards to applicants from the biomedical, behavioral, public health, social sciences, computer and information sciences, and engineering disciplines to help them to create, expand and strengthen education and training programs focused on AI/ML and related competencies, and/or their application to minority health disparities and research. The DTSC Curriculum Development pilot program will provide grants to faculty, researchers and practitioners from the biomedical, behavioral, public health, social sciences, computer and information sciences, and engineering disciplines to develop socially and culturally relevant open source content and curriculum. This program encourages the development of curriculum focused on minority health disparities in behavioral health, cardiometabolic health, and cancer, and curriculum that exposes students to: 1) the intersection of AI/ML and the use of social and environmental determinants of health (SEDoH) 2) structural barriers to equity; 3) race, ethnicity, gender, and/or sexual orientation as constructs that affect health outcomes; and 4) the incorporation of hands on labs and projects that use EHR data.

The Outreach and Workforce Development Pilot Program (OWDPP) will help develop a diverse, equitable and inclusive AI/ML workforce as well as increase the knowledge, awareness and trust of AI/ML through engagement. Proposed pilot training activities should address a specific issue related to minority health and/or health disparities, particularly around the AIM AHEAD North Star areas: behavioral health, cardiometabolic health, and cancer. Understandably, some proposed OWDPP training activities may need to introduce foundational data science concepts and tools more generally earlier in the educational pipeline (ie, K-8). Proposed outreach activities may complement ongoing training and education occurring at the applicant institution, but the proposed activities must specifically address how artificial intelligence/machine learning will be integrated into training activities to address research into health disparities. We are interested in a range of training paradigms such as but certainly not limited to 1) Community engagement-related projects that build awareness of the intersection of AI/ML with social and environmental determinants of health (SEDOH), structural and racial equity, race, gender, and ethnicity as constructs in determining health related outcomes. and/or 2) Hands-on exposure and/or interdisciplinary research experiences for K-12, undergraduate students, post baccalaureate students, masters students, predoctoral students, postdoctoral fellows, and/or early-stage faculty from groups underrepresented in the biomedical and behavioral sciences.

Link to the Outreach and Workforce Development Call for Pilot Programs: https://docs.google.com/document/d/1YydgS4BUqDfLnNJRRLS-kxPbHReEqOzBO9kk1RcYI0k/edit?usp=sharing

The AIM-AHEAD Faculty Teaching Buy-out Pilot Program, issued by the DSTC, will provide grants to faculty from the biomedical, behavioral, public health, social sciences, computer and information sciences, and engineering disciplines to be released from instruction by their Chair or Director in exchange for funding provided by this award. A portion of the funding should be made available to pay for a substitute instructor, while the faculty member designs and develops the socially and culturally relevant open-source curriculum for a newly proposed course. It is anticipated that this course buyout will be instituted in the Fall 2022 semester, and that the new course be delivered in the Spring 2023 semester. This CFPP encourages the development of curriculum that exposes students to: 1) the intersection of AI/ML and health equity including social and environmental determinant of health (SEDoH); 2) structural barriers to equity; 3) race, ethnicity, gender, and/or sexual orientation as constructs that affect health outcomes; and 4) the incorporation of hands-on labs and projects that use EHR data.

The AIM-AHEAD Data Science Training Core Professional Development Fellow (AA-PDF) Pilot Program is hosted at the University of Maryland, College Park, which is part of the DSTC. The AA-PDF will provide training grants to support professional development activities that encourage the participation of underrepresented individuals from health-related institutions, to improve AI/ML implementation and promote health equity. This program encourages the amplification of the professional development program focused on minority health disparities in behavioral health, cardiometabolic health, and cancer, and a curriculum that draws learners' attention to (1) identify the appropriate AI tool for different contexts and applications in healthcare settings; (2) leverage AI-based clinical decision support tools to reduce disparities in healthcare; (3) manage the organization (both human and technical) resources needed for AI, measuring performance and outcomes, and justifying the return on investment; (4) build high-performance ML/AI teams and creating the right organizational culture for AI-enabled transformation; (5) translate cutting edge AI knowledge into equity-enhancing projects. Open to all healthcare working professionals, the AA-PDF program covers topics in Health Equity and Fairness, Healthcare Policy and Finance, Healthcare Operations and Marketing, Health Information Technology, Deep Learning based AI, as well as Leadership in AI Transformation in Healthcare. The AA-PDF program will provide a 360-degree view of the healthcare ecosystem, as it continues to evolve and produce an increasing amount of yet-unharnessed data power.

The AIM-AHEAD Data Science Core (DSTC) Conference, Workshop & Speaker Series Pilot Program is hosted at the University of Maryland, College Park, which is part of the DSTC. The AIM-AHEAD Data Science Training Core (DSTC) Conference, Workshop & Speaker Series Pilot Program will grant opportunities to support existing or new activities in the form of conferences, workshops, and speaker series focused on AI/ML and related competencies, and/or their application to minority health disparities, to further encourage the participation of underrepresented individuals as recognized by the National Institutes of Health (NIH), from all types of healthcare institutions. The activities proposed under this program should be aligned with the following learning objectives. (1) Introducing concepts and/or tools for AI/ML applications in healthcare-related settings; (2) Disseminating information about AI-based clinical decision support tools to reduce disparities in healthcare; (3) Understanding the organizational (both human and technical) resources needed for AI, measuring performance and outcomes, and justifying the return on investment; (4) Networking with high-performance AI/ML teams and creating the right organizational culture for AI-enabled transformation; (5) Sharing results of equity-enhancing projects using cutting edge AI resources. The proposed activity should be focused on minority health disparities in behavioral health, cardiometabolic health, and cancer.

The Bridge Fellows program is designed to prepare students for the rigors of data science without having to complete a separate and full course of study or degree program in preparation for the data and computer science curriculums. As a result, the bridge program is expected to accelerate the time to degree for non-STEM students. The AIM-AHEAD Data Science Training Core (DSTC) Bridge Fellows Pilot Program will provide scholarships in the form of tuition assistance to expand participation of undergraduates from non-CS/Eng/Math disciplines to enter into Master’s programs in Data Science or Computer Science. The Bridge Fellows program is designed to prepare students for the rigors of data science without having to complete a separate and full course of study or degree program in preparation for the data and computer science curriculums.

Scroll to top