DSTC: Staying Current with Cutting Edge AI Training Modules
Cutting Edge AI Training
Course Description
Intended Audience
This training series is designed for professionals, researchers, and policymakers within the AIM-AHEAD consortium and the broader healthcare and AI communities who seek to stay current with advancements in artificial intelligence. The program is particularly relevant for:
Healthcare professionals and clinical researchers integrating AI into medical decision-making.
Data scientists, AI researchers, and engineers working on AI applications in healthcare.
Industry professionals and technology leaders shaping AI-driven healthcare innovations.
Graduate students and early-career professionals seeking foundational and advanced knowledge in AI for healthcare.
By engaging with this program, participants will gain the expertise necessary to navigate the evolving AI landscape and contribute to the responsible and effective deployment of AI in healthcare.
Course Learning Objectives
Upon completing the Staying Current with Cutting-Edge AI (CEA) Training Series, participants will be able to:
Understand AI's Evolution and Impact
Trace the historical development of AI, with a focus on its rapid advancements and applications in healthcare.
Analyze key AI breakthroughs, including Generative AI, foundation models, and human-AI collaboration.
Develop a Robust AI Mindset
Define and strengthen robustness in AI-driven healthcare applications.
Understand challenges to robust AI in clinical settings, including real-world variability and data integrity.
Apply strategies to enhance robustness through diverse data, proactive testing, and transparent, adaptable system design.
Enhance Technical Competence in AI for Healthcare
Gain expertise in AI model development, including Large Language Models (LLMs) and multimodal AI models.
Understand AI’s role in biomedical imaging, clinical data curation, and harmonization.
Learn techniques for integrating diverse data sources.
Apply AI in Healthcare Research and Practice
Leverage AI to improve clinical decision-making and patient outcomes.
Analyze real-world case studies demonstrating the impact of AI on improving healthcare delivery and outcomes.
Explore the latest tools, frameworks, and methodologies for AI-driven healthcare research.
Prepare for Future AI Innovations
Examine emerging trends in AI, including augmented intelligence and human-AI teaming.
Evaluate the implications of AI’s continued evolution on labor, policy, and clinical workflows.
Position themselves as informed stakeholders, shaping the effective use of AI in healthcare.
This training series aims to bridge the knowledge gap in AI, equipping participants with both theoretical insights and practical skills to responsibly and effectively leverage AI for advancing health research and innovation.
Course Structure
Module 1: Overview of AI trajectory: History and Development
Module 2: Robust AI
Module 3: Generative AI and Large Language Models
Module 4: Human-AI teaming
Module 5: Healthcare Data for AI: Data curation, cleaning, and harmonization
Module 6: Multimodal Data AI Models for Health Research
Course Description
The Data Science Training Core (DSTC) has the mission to identify training needs within the AIM-AHEAD consortium and actively develop resources to bridge the gaps.
One of the major knowledge gaps is driven by the rapid progression of Artificial Intelligence. This acceleration is exemplified by breakthroughs in Generative AI applications like ChatGPT, Bard, and Llama. For instance, the progress of machine learning and deep neural networks has outpaced the formulation of comprehensive guidelines and policies necessary for governing their effective use. AIM-AHEAD stakeholders need to keep up with the advances of AI.
Recognizing this crucial gap, our training program: Staying Current with Cutting Edge AI (CEA) Training Series aims to address the rapidly evolving landscape of AI. Through collaborative efforts among experts, policymakers, and industry leaders, participants will gain the expertise needed to bridge existing gaps and contribute to the robust development and deployment of AI technologies.
Through this initiative, DSTC aims to bring awareness of the advances of AI technology and equip participants with the knowledge and skills necessary to navigate the dynamic landscape of AI in healthcare and contribute meaningfully to health research. Each module is meticulously designed to unravel the intricacies of breakthrough technologies and cutting-edge techniques in AI applied to healthcare.
One of the major knowledge gaps is driven by the rapid progression of Artificial Intelligence. This acceleration is exemplified by breakthroughs in Generative AI applications like ChatGPT, Bard, and Llama. For instance, the progress of machine learning and deep neural networks has outpaced the formulation of comprehensive guidelines and policies necessary for governing their effective use. AIM-AHEAD stakeholders need to keep up with the advances of AI.
Instrumental Persons
We would like to recognize and express our gratitude to the following people who shared in the creation and implementation of this course:
Guodong Gao: Course Director
Legand Burge: DSTC Lead, AIM-AHEAD MPI
Nawar Shara: Course Director
Toufeeq Ahmed Syed, PhD: Course Director
Upasna Sagar, BDS, MHA: Program Manager, CDHAI, Johns Hopkins University, DSTC
Prabhjeet Singh, BDS, MSPH: Program Manager, MedStar, DSTC
- Paul Warhurst, PhD: Communications Hub, AIM-AHEAD
- Cara Morrison: Communications Hub, AIM-AHEAD
Funding
The AIM-AHEAD program is funded by NIH, Agreement No. 1OT2OD032581-01. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.