不良研究所

Digital Health | May 29-31, 2024

鈥淭he course was very helpful. It gave clear insights on the trend of digital health in the world and where studies are lacking for researchers.鈥�

-Digital Health course participant

COURSE FORMAT

Hybrid. Course will be live to both the in-person and online participants approximately 9:00am-3:00pm (Montreal time) each day May 29 鈥� May 31, 2024. All content will be recorded and accessible to participants until July 1, 2024.

DESCRIPTION

The health care industry is at the threshold of a massive disruption that is increasingly catalyzed by the COVID-19 pandemic. The scope of change and transformation brought about by innovations is unprecedented. Wearables and Internet of Things (IoT) enabled platforms have improved remote patient monitoring and monitoring for wellness. Smart Applications (Apps) have demonstrated evidence of improved linkages and retention of patients in care, expanded access to unreached populations, improved documentation of health-related metrics and overall engagement in health care. Machine learning has improved prediction. 3D modeling and 3D printing have generated a blueprint for changes in drugs, devices, prosthetics, and hearing aids. High-value care (convenient, targeted, personalized, efficient, and cost-saving) is available for the billions with access to the internet. Convergence of sorts of many exciting innovative developments in parallel is being accelerated by the prolongation of the COVID-19 pandemic.

Note May 27th: Enrollment is closed for this course.

CONTENT

This course will cover topics in digital health and machine learning as they relate to connected Internet-of-things solutions, machine learning solutions, predictive analytics, meta-verse, digital twins, connected diagnostics, and challenges/successes faced in the integration of digital health solutions. Participants will learn evidence generation with these solutions and industry perspectives on how these solutions are poised to create a massive disruption in healthcare delivery in the years to come.

Content will cover a wide variety of topics from population health/preventative medicine to clinical medicine/virtual health and telemedicine. We will also showcase clinical decision support systems with algorithms to Metaverse based immersive experience. Students will learn about the novel innovations, evaluations, and implementation evidence, and discuss challenges & barriers to scale-up, and sustainability.

The course format includes a mix of plenary talks, engaging panel discussions, and showcases innovative products and services from innovators, industry, academics, data analysts, and health care organizations.

COURSE DIRECTOR

Nitika Pant Pai, MD, MPH, PhD
Associate Professor, Department of Medicine, 不良研究所
Divisions of Clinical Epidemiology, Experimental Medicine & Infectious Diseases.
Center for Outcomes Research and Evaluation, MUHC Research Institute

PREVIOUS COURSE FACULTY

• Raghu Dharmaraju - AI for Social Good and Lancet Citizens Commission
• Nara Sundararajan 鈥� Google
• Rigveda Kadam 鈥� Digital health Lead, Foundation for Innovative Diagnostics, Geneva
• Brian Wong 鈥� Lancet and Financial Times Commission
• Samira Abbasgholizadeh-Rahimi 鈥� MILA and 不良研究所
• Anurag Agrawal 鈥� Asoka University; Co-Chair The Lancet Commission
• Miguel Armengol de la Hoz 鈥� Ministry of Health, Spain
• Leo Anthony Celi 鈥� PloS Digital Health; Harvard University
• Ruchi Dass - Health Cursor Consulting Group
• Judy Wawira Gichoya 鈥� Emory University
• Sruti Sridhar 鈥� Qure.ai
• David Benrimoh 鈥� Aifred Health
• Patrick O鈥橬eill - LFAnt
• Zelalem Temesgen 鈥� Mayo Clinic
• Hope Watson 鈥� Current Health
• Amalia M. Issa 鈥� 不良研究所

Faculty are still being confirmed and there may be changes to the above list.

OBJECTIVES

• Identify exemplars of digital health innovations implemented globally and discuss the implementation at scale and sustainability of promising digital health innovations.
• Convene discussions on data harmonization and governance, data access, sharing, and ownership to inform the direction of future practice, policy.
• Discuss funding initiatives for big data and digital health.
• Explore how to generate evidence in support of innovations for future implementation.
• Discuss key areas in digital health and machine learning.

TARGET AUDIENCE

This course appeals to a wide range of participants including:

• Innovators
• Entrepreneurs
• Students, trainees, Fellows
• Researchers and academics
• Clinicians
• Clinical Administrators, Healthcare Organizations CIO, CTO, CDO, CDGHO
• Students and fellows
• Product developers
• Funders and public health agency officials
• Patient advocates and clinical champions
• Policy makers
• Non-profit organizations and foundations
• Industry

ENROLMENT

Limited to 100 online participants and 75 in-person participants.