PhD seminar – Ninon Burgos

Venue: Centre Broca

Ninon Burgos
CNRS
Paris Brain Institute

Invited by Natalia Khotkina (Sanpsy)

Title

AI and Neuroimaging for Diagnosis in the Real World: Lessons from the AP-HP Data Warehouse

Abstract

The integration of artificial intelligence and neuroimaging opens new perspectives for diagnosing neurological diseases. However, most machine learning approaches have been validated on research datasets, and their generalisation to clinical routine remains unclear. Hospital data warehouses offer considerable volumes of real-world data, enabling evaluation in routine care settings. We are currently exploiting data from the Greater Paris hospitals (AP-HP, comprising 39 hospitals and millions of patients) to develop AI tools for biomarker identification and disease prediction. This presentation will address the challenges we face related to imaging data quality and heterogeneity, and highlight the solutions we propose.

Biosketch

Ninon Burgos is a CNRS research director at the Paris Brain Institute, co-head of the ARAMIS Lab, and a fellow of PR[AI]RIE, the PaRis Artificial Intelligence Research InstitutE.

She completed her PhD in 2016 at University College London, and obtained her Habilitation (HDR) from Sorbonne Université in 2022. In 2019, she received the ERCIM Cor Baayen Young Researcher Award.
Her research focuses on the processing and analysis of medical images, the use of images to guide diagnosis, and the application of these methods to the clinic. In particular, she has contributed to: i) anomaly detection using both traditional image processing techniques and deep generative models, ii) the translation of machine learning approaches for quality control and computer-aided diagnosis into clinical practice, iii) reproducible medical image processing and computer-aided diagnosis with machine learning, and iv) the development of open-source software.

Key publications related to the talk