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Scientific Fields
Diseases
Organisms
Applications
Technique
Date
04
Oct 2024
Time
09:30:00
Address
Building: Emile Duclaux Room: Lecture Hall
Location
2024-10-04 09:30:00 2024-10-04 18:00:00 Europe/Paris Symposium ATC-IA – Artificial Intelligence in Biology and Health – Edition 2024 The Targeted Technological Action on Artificial Intelligence (ATC-IA) is organizing the second edition of its Symposium ” Artificial Intelligence in Biology and Health. It will be held on 4th October 2024 in the Émile […] Laura Cantini laura.cantini@pasteur.fr

About

The Targeted Technological Action on Artificial Intelligence (ATC-IA) is organizing the second edition of its Symposium ” Artificial Intelligence in Biology and Health. It will be held on 4th October 2024 in the Émile Duclaux lecture hall at the Institut Pasteur campus. The symposium will bring together researchers working at the intersection of AI with biomedical sciences to discuss opportunities and challenges in this exciting and rapidly evolving field.

There will be a dozen talks on applications of AI to biology and Health. There will also be posters session (with poster prizes).The symposium will include two invited keynote talks by eminent speakers:
Anne-Florence BITBOL (EPFL, Lausanne, Switzerland)
Jean-Remi KING (ENS-PSL, Paris, France)

Registration (free but mandatory) and the call for abstracts
to select speakers and posters are now open

↗️ REGISTRATION & ABSTRACT SUBMISSION FORM 

Deadline for abstract submission: 27th May 2024 – midnight
Deadline for public registration: 13th September -midnight

Artificial intelligence (AI) methods such as deep learning have fueled breakthroughs in many data-intensive fields, such as computer vision, speech recognition or question-and-answer systems, as recently illustrated by ChatGPT. AI also holds enormous potential for biology and health. Indeed, AI-powered methods can accurately predict 3D protein structures from their DNA sequence, diagnose skin cancer from photographs, predict patient outcomes or help design new drugs… AI can also integrate large and complex data sets including genomics, transcriptomics and proteomics data and mine them for new insights.

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