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LaTiM: Longitudinal representation learning in continuous-time models to
  predict disease progression

LaTiM: Longitudinal representation learning in continuous-time models to predict disease progression

10 April 2024
Rachid Zeghlache
Pierre-Henri Conze
Mostafa EL HABIB DAHO
Yi-Hsuan Li
Hugo Le Boité
R. Tadayoni
Pascale Massin
B. Cochener
Alireza Rezaei
Ikram Brahim
G. Quellec
M. Lamard
ArXivPDFHTML

Papers citing "LaTiM: Longitudinal representation learning in continuous-time models to predict disease progression"

10 / 10 papers shown
Title
Longitudinal Self-supervised Learning Using Neural Ordinary Differential
  Equation
Longitudinal Self-supervised Learning Using Neural Ordinary Differential Equation
Rachid Zeghlache
Pierre-Henri Conze
Mostafa EL HABIB DAHO
Yi-Hsuan Li
Hugo Le Boité
...
Pascale Massin
B. Cochener
Ikram Brahim
G. Quellec
M. Lamard
63
4
0
16 Oct 2023
LMT: Longitudinal Mixing Training, a Framework to Predict Disease
  Progression from a Single Image
LMT: Longitudinal Mixing Training, a Framework to Predict Disease Progression from a Single Image
Rachid Zeghlache
Pierre-Henri Conze
Mostafa EL HABIB DAHO
Yi-Hsuan Li
Hugo Le Boité
...
Pascale Massin
B. Cochener
Ikram Brahim
G. Quellec
M. Lamard
69
4
0
16 Oct 2023
LSOR: Longitudinally-Consistent Self-Organized Representation Learning
LSOR: Longitudinally-Consistent Self-Organized Representation Learning
J. Ouyang
Qingyu Zhao
Ehsan Adeli
Wei Peng
Greg Zaharchuk
K. Pohl
60
1
0
30 Sep 2023
Learning Spatio-Temporal Model of Disease Progression with NeuralODEs
  from Longitudinal Volumetric Data
Learning Spatio-Temporal Model of Disease Progression with NeuralODEs from Longitudinal Volumetric Data
Dmitrii Lachinov
A. Chakravarty
C. Grechenig
U. Schmidt-Erfurth
Hrvoje Bogunović
45
11
0
08 Nov 2022
Metadata-enhanced contrastive learning from retinal optical coherence
  tomography images
Metadata-enhanced contrastive learning from retinal optical coherence tomography images
R. Holland
Oliver Leingang
Hrvoje Bogunović
Sophie Riedl
L. Fritsche
...
U. Schmidt-Erfurth
S. Sivaprasad
A. Lotery
Daniel Rueckert
Martin J. Menten
38
9
0
04 Aug 2022
Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease
  Progression
Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease Progression
Zhaozhi Qian
W. Zame
L. Fleuren
Paul Elbers
M. Schaar
OOD
38
54
0
05 Jun 2021
Predicting Risk of Developing Diabetic Retinopathy using Deep Learning
Predicting Risk of Developing Diabetic Retinopathy using Deep Learning
Ashish Bora
Siva Balasubramanian
Boris Babenko
S. Virmani
Subhashini Venugopalan
...
D. Webster
A. Varadarajan
N. Hammel
Yun-Hui Liu
Pinal Bavishi
20
143
0
10 Aug 2020
Bootstrap your own latent: A new approach to self-supervised Learning
Bootstrap your own latent: A new approach to self-supervised Learning
Jean-Bastien Grill
Florian Strub
Florent Altché
Corentin Tallec
Pierre Harvey Richemond
...
M. G. Azar
Bilal Piot
Koray Kavukcuoglu
Rémi Munos
Michal Valko
SSL
299
6,718
0
13 Jun 2020
GRU-ODE-Bayes: Continuous modeling of sporadically-observed time series
GRU-ODE-Bayes: Continuous modeling of sporadically-observed time series
E. Brouwer
Jaak Simm
Adam Arany
Yves Moreau
SyDa
CML
AI4TS
89
292
0
29 May 2019
Neural Ordinary Differential Equations
Neural Ordinary Differential Equations
T. Chen
Yulia Rubanova
J. Bettencourt
David Duvenaud
AI4CE
276
5,024
0
19 Jun 2018
1