Useful information

The AI4Health Summer School is an international event that will be held in English

Contact

Technical Committee

Mail: ai4h2025@premc.org
Phone: +331.46.60.89.40

Scientific Committee

Pratical Information

Dates

  • June 30th to July 3rd at Paris Sciences & Lettres Université for on-site participants
  • June 30th online for remote and hybrid participants

Venue

  • The event will take place at the Paris Sciences & Lettres Université – “Estrapade” Auditorium
  • 16 bis rue de l’Estrapade, 75005 Paris
  • Registration desks will be located at the entrance of the hall
  • The program with the names of the rooms where the sessions will take place will be displayed on site
  • Poster sessions and catering will take place in the main Hall and behind the lecture theatre.

Getting to Estrapade – Paris Sciences & Lettres Université

    • Paris can be reached by train or plane.
      Airports: Paris Charles De Gaulle (CDG), Paris Orly (ORY)
    • The closest public transport stations are:
      • M10 – stop at “Cardinal Lemoine”
      • M7 – stop at “Place Monge”
      • RER B – stop at “Luxembourg”
      • Bus lines:
        • 21: stop at “Luxembourg”
        • 24: stop at “Musée et Institut Curie”
        • 84 and 89: stop at “Panthéon”
    • If you plan to arrive by car, please note that parking may be limited and charged in this area of Paris as there will not be a specific parking lot for this event. 
    • Plan your route with Google Maps or City Mapper.

Program

  • The first day will be dedicated to world renowned hospital and international experts’ keynotes on AI innovation for cares and research (June 30th), followed by dynamic round tables on the latest advancement in the filed of AI applied to health.
  • Three following days of scientific courses and hands-on sessions, led by international experts and their team, for on-site participants:  2x1h30 courses in a row in the mornings, and 2 parallel hands-on sessions of 3 hours each, in smaller groups corresponding to the morning classes, in the afternoons.
  • 1 poster hallway showcasing the best abstract from attendees, exclusively on-site, with a prize of 500€ value for the best poster (elected by the AI4Health scientific committee).
Who can apply

The school is intended for students (first & second year masters, PhD), post-docs, academics, researchers, members of public institutions, and professionals. 

For on-site participants for the four days, at least basic knowledge in machine learning (using Python or any other language) is required as this is necessary to attend and benefit from the hands-on sessions.

Poster abstract guidelines

Poster hallway

AI4Health offers on site participants the opportunity to submit abstracts during the registration process. These will be reviewed by the AI4Health scientific committee. Please note that submitting an abstract is not required to register on site, however it is highly encouraged.

The abstract cannot be longer than 350 words distributed between introduction, material and methods, and results/conclusion (excluding authors and affiliations). All abstracts must include a title, a full list of authors and affiliations.

You may submit your abstract until the on-site registration closes, on April 18th. The selection committee will review all applications. If your application to participate on-site is accepted and if your abstract is selected, you will be able to display your poster with other on-site participants and experts. 

You will be required to print your poster (A0 in portrait orientation only) and bring it on site the day before the poster session. Please note that printing on site will not be possible.

The AI4H scientific committee will reward the best abstract/poster with a prize of 500€ value.

Please note that posters will exclusively be showcased on-site in a hallway.

Past AI4H schools

Discover the 2022 speakers

Alessandro Blasimme (Switzerland)

« Artificial intelligence in medicine: an ethical perspective »

Tobias Gauss (France)

« Machine learning in the triage of major trauma, the Traumatrix project »

Anna Goldenberg (Canada)

“AI for healthcare time series”

Bjoern Menze (Switzerland)

« Deep learning for medical image data – from images to structures to graphs »

Sébastien Ourselin (UK)

« Learning across 16M patients: platforms

Petra Ritter (Germany)

« How complex simulations augment

Arnaud Rosier (France)

« Implicity: how an AI concept becomes an approved medical device used daily by healthcare professionals »

Andrzej Rys (Belgium)

« Digital health: policy and regulatory landscape in the European Union and globally »

Uri Shalit (Israel)

« The basics of causal inference for health applications »

Mihaela Van der Schaar (UK)

« The future of personalized medicine and its implications on the healthcare systems: A machine learning perspective »

Serena Villata (France)

« Clinical Text Analysis: Methods and Applications »

Statistics from 2023