AI in Public Health: Applications and Challenges

Dans le cadre de l’événement "Applied Machine Learning Days", Unisanté organise une intervention intitulée "AI in Public Health: Applications and Challenges". L'événement aura lieu en anglais. 

Topic

AI in Public Health: Applications and Challenges

Public health is the branch of medicine dealing with the health of the population as a whole. Its objectives are to keep people healthy and prevent illness, injury, and premature death through various actions, including disease prevention, health promotion, illness and injury surveillance and tracking, or emergency preparedness, coordinated public policies, community education, and targeted research.

Public health fundamentally relies on data gathered from observations and experimental research to inform and implement evidence-based interventions that improve community health outcomes. By leveraging data, public health efforts can become more proactive, personalized, and effective, leading to better health outcomes on a community and global level.
In recent decades, the integration of artificial intelligence (AI) in public health has provided new capabilities for synthetizing evidence, processing and analyzing large data sets efficiently, detecting complex patterns, and offering predictions about future health events based on existing and historical data.

While AI holds significant promise for enhancing public health, its integration comes with notable challenges, including ensuring data privacy, addressing potential biases in algorithms, and maintaining transparency in AI-driven decision-making processes.

This conference track offers a comprehensive exploration of AI in the field of Public Health. Participants will gain insights into AI's diverse applications, from disease prevention to crisis management. Our aim is to equip professionals with knowledge about the latest AI innovations and their practical implications (opportunities and challenges) in public health. Each presentation in this track will describe the AI algorithm and detail its public health applications.

Session Chairs

• Marie-Annick LE POGAM, Unisanté - Organizer
• Valérie PITTET, Unisanté - Organizer

Line Up

• 11:00 - 11:05 Track introduction
  • Marie-Annick LE POGAM, Unisanté, Switzerland
  • Valérie PITTET, Unisanté, Switzerland
• 11:05 - 11:25 AI and Public Health: Current trends and perspectives
  • Marie-Annick LE POGAM, Unisanté, Switzerland
  • Valérie PITTET, Unisanté, Switzerland
• 11:25 - 11:55 AI for personnalized health education and prevention of chronic diseases
  • Cyril GAUTHIER, Nuvee, France
  • Sébastien BIAUDET, The Humanizers, France
• 11:55 - 12:15 AI for enhanced systematic review and evidence synthesis
  • Ian SHEMILT, EPPI-Centre, United Kingdom
• 12:15 - 12:25 Climate analytics for assessing current and future health threats
  • Christopher IRRGANG, Robert Koch Institute, Germany
• 12:25 - 12:30 Track conclusion
  • Valérie PITTET, Unisanté, Switzerland

À propos de l'Applied Machine Learning Days

Cet événement d'envergure attire chaque année des participantes et participants de plus de 40 pays issus de l'industrie, du monde universitaire et des pouvoirs publics. 

Organisé sur quatre jours, du 23 au 26 mars 2024, cette édition 2024 vous offrira l'opportunité de connaître les dernières recherches et perspectives en matière d'apprentissage automatique, mais aussi d'échanger des connaissances avec des expertes et experts dans le domaine. 

• Site internet de l'Applied Machine Learning Days (AMLD)