AI/ML in Digital Health Technologies (DHTs)

The use cases of artificial intelligence and machine learning (AI/ML) in digital health technologies to improve healthcare through software. Understand the challenges, and identify the gaps. Connect different stakeholders, share knowledge, and advance in developing AI/ML in DHTs.  

DHTs are revolutionising the healthcare industry, with AI/ML playing a key role in the development of new solutions. With more applications of AI/ML in practice, from optimising workflows to improving diagnostic capabilities, the collaborations to learn from the use cases and the partnership to overcome challenges are urgently needed.

The integrated effort to study real-world applications will ensure the emerging technologies are used effectively and in compliance with relevant guidelines and regulations.

Sub-Team

Forum Topic

Lead

GA

Generative AI in healthcare

Jeffrey Lavenberg

AP

Application of AI/ML in precision medicine (includes RWE)

Shraddha Thakkar

RL

Regulatory landscape of AI/ML in DHTs (current landscape, knowledge gaps, best practices for regulatory submissions, challenges of regulating AI)

Richard Baumgartner

MD

AI/ML models (logistic regression, support vector machines, decision tree, convolutional neural networks, etc.)

Hanming Tu

UC

Challenges of use of AI/ML in DHTs (ethical concerns, privacy issues/cybersecurity, misuse of data, complexity of data management including data interoperability, etc.)

Jessica Hu

SD

Software-driven medical devices

Anders Vidstrup