Zobrazeno 1 - 10
of 2 734
pro vyhledávání: '"Massin, P."'
LaTiM: Longitudinal representation learning in continuous-time models to predict disease progression
Autor:
Zeghlache, Rachid, Conze, Pierre-Henri, Daho, Mostafa El Habib, Li, Yihao, Boité, Hugo Le, Tadayoni, Ramin, Massin, Pascal, Cochener, Béatrice, Rezaei, Alireza, Brahim, Ikram, Quellec, Gwenolé, Lamard, Mathieu
This work proposes a novel framework for analyzing disease progression using time-aware neural ordinary differential equations (NODE). We introduce a "time-aware head" in a framework trained through self-supervised learning (SSL) to leverage temporal
Externí odkaz:
http://arxiv.org/abs/2404.07091
Autor:
Zeghlache, Rachid, Conze, Pierre-Henri, Daho, Mostafa El Habib, Li, Yihao, Rezaei, Alireza, Boité, Hugo Le, Tadayoni, Ramin, Massin, Pascal, Cochener, Béatrice, Brahim, Ikram, Quellec, Gwenolé, Lamard, Mathieu
Pre-training strategies based on self-supervised learning (SSL) have proven to be effective pretext tasks for many downstream tasks in computer vision. Due to the significant disparity between medical and natural images, the application of typical SS
Externí odkaz:
http://arxiv.org/abs/2403.16272
Autor:
Edenhofer, Gordian, Frank, Philipp, Roth, Jakob, Leike, Reimar H., Guerdi, Massin, Scheel-Platz, Lukas I., Guardiani, Matteo, Eberle, Vincent, Westerkamp, Margret, Enßlin, Torsten A.
Publikováno v:
Journal of Open Source Software, volume 9(98), year 2024, page 6593
Imaging is the process of transforming noisy, incomplete data into a space that humans can interpret. NIFTy is a Bayesian framework for imaging and has already successfully been applied to many fields in astrophysics. Previous design decisions held t
Externí odkaz:
http://arxiv.org/abs/2402.16683
Autor:
Zeghlache, Rachid, Conze, Pierre-Henri, Daho, Mostafa El Habib, Li, Yihao, Boité, Hugo Le, Tadayoni, Ramin, Massin, Pascal, Cochener, Béatrice, Brahim, Ikram, Quellec, Gwenolé, Lamard, Mathieu
Publikováno v:
Predictive Intelligence in Medicine. PRIME 2023. Part of the Lecture Notes in Computer Science book series (LNCS,volume 14277)
Longitudinal analysis in medical imaging is crucial to investigate the progressive changes in anatomical structures or disease progression over time. In recent years, a novel class of algorithms has emerged with the goal of learning disease progressi
Externí odkaz:
http://arxiv.org/abs/2310.10431
Autor:
Zeghlache, Rachid, Conze, Pierre-Henri, Daho, Mostafa El Habib, Li, Yihao, boite, Hugo Le, Tadayoni, Ramin, Massin, Pascal, Cochener, Béatrice, Brahim, Ikram, Quellec, Gwenolé, Lamard, Mathieu
Publikováno v:
Machine Learning in Medical Imaging. MLMI 2023
Longitudinal imaging is able to capture both static anatomical structures and dynamic changes in disease progression toward earlier and better patient-specific pathology management. However, conventional approaches rarely take advantage of longitudin
Externí odkaz:
http://arxiv.org/abs/2310.10420
Publikováno v:
Earth, Planets and Space, Vol 76, Iss 1, Pp 1-14 (2024)
Abstract Seismic monitoring matters both for research and for populations living in areas of seismic hazard; however, it comes with a cost that is not fully affordable for developing countries. Compared to classical approaches with very quiet sites a
Externí odkaz:
https://doaj.org/article/e38a5b2f9f604819b84e33e7c531b1e5
Autor:
Zeghlache, Rachid, Conze, Pierre-Henri, Daho, Mostafa El Habib, Tadayoni, Ramin, Massin, Pascal, Cochener, Béatrice, Quellec, Gwenolé, Lamard, Mathieu
Longitudinal imaging is able to capture both static anatomical structures and dynamic changes in disease progression towards earlier and better patient-specific pathology management. However, conventional approaches for detecting diabetic retinopathy
Externí odkaz:
http://arxiv.org/abs/2209.00915
Autor:
M. Böse, L. Danciu, A. Papadopoulos, J. Clinton, C. Cauzzi, I. Dallo, L. Mizrahi, T. Diehl, P. Bergamo, Y. Reuland, A. Fichtner, P. Roth, F. Haslinger, F. Massin, N. Valenzuela, N. Blagojević, L. Bodenmann, E. Chatzi, D. Fäh, F. Glueer, M. Han, L. Heiniger, P. Janusz, D. Jozinović, P. Kästli, F. Lanza, T. Lee, P. Martakis, M. Marti, M.-A. Meier, B. Mena Cabrera, M. Mesimeri, A. Obermann, P. Sanchez-Pastor, L. Scarabello, N. Schmid, A. Shynkarenko, B. Stojadinović, D. Giardini, S. Wiemer
Publikováno v:
Natural Hazards and Earth System Sciences, Vol 24, Pp 583-607 (2024)
Scientists from different disciplines at ETH Zurich are developing a dynamic, harmonised, and user-centred earthquake risk framework for Switzerland, relying on a continuously evolving earthquake catalogue generated by the Swiss Seismological Service
Externí odkaz:
https://doaj.org/article/c6c65e68ad6243e0803eeb1cdcb86dde
Autor:
Fadi Alkhami, Gauthier Borderie, Ninon Foussard, Alice Larroumet, Laurence Blanco, Marie-Amélie Barbet-Massin, Amandine Ferriere, Claire Ducos, Kamel Mohammedi, Sami Fawaz, Thierry Couffinhal, Vincent Rigalleau
Publikováno v:
Cardiovascular Diabetology, Vol 23, Iss 1, Pp 1-4 (2024)
Abstract Chen et al. recently related the skin autofluorescence (SAF) of Advanced Glycation End-products to subclinical cardiovascular disease in the 3001 participants from the general population (Rotterdam study), with a particularly close relations
Externí odkaz:
https://doaj.org/article/de8a9b2b8d884dcba04c562fcdb425b8
Publikováno v:
Seismica, Vol 3, Iss 1 (2024)
It is increasingly common for seismic networks to operate multiple independent automatic algorithms to characterise earthquakes in real-time, such as in earthquake early warning (EEW) or even standard network practice. Commonly used methods to select
Externí odkaz:
https://doaj.org/article/f2c821ed010a42b29078bcd1cb5139e0