Posts

The cruel dilemma of health data in the ai era: privacy or equity?

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Federated learning is a way to collaboratively train artificial intelligence models. It thus represents a possible solution to AI biases, often caused by training said models on samples that lack diversity. In the healthcare sector, these biases can lead to problems of equity between patients. The EQUIHid project explores how federated learning can help develop more equitable healthcare services.
cancer

A biocluster to boost innovation in cancer treatment

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Paris Saclay Cancer Cluster offers a wide range of scientific and technical solutions to support the challenging field of research aimed at fighting cancer. Telecom Paris is invested in this ambitious initiative, which strengthens ties between those driving innovation in oncology and provides access to a combination of technological platforms, databases, expertise and training opportunities.
Tatouage des données de santé, health data

Encrypting and watermarking health data to protect it

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As medicine and genetics make increasing use of data science and AI, the question of how to protect this sensitive information is becoming increasingly important to all those involved in health. A team from the LaTIM laboratory is working on these issues, with solutions such as encryption and watermarking. It has just been accredited by Inserm.
données de santé, health data

Speaking the language of health data to improve its use

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The world of healthcare has extensive databases that are just waiting to be used. This is one of the issues Benjamin Dalmas, a data science researcher at Mines Saint-Étienne, is exploring in his work. His main objective is to understand the…