Machine and deep learning for longitudinal biomedical data: a review of methods and applications
A Cascarano, J Mur-Petit… - Artificial Intelligence …, 2023 - Springer
Exploiting existing longitudinal data cohorts can bring enormous benefits to the medical
field, as many diseases have a complex and multi-factorial time-course, and start to develop …
field, as many diseases have a complex and multi-factorial time-course, and start to develop …
Predictive models for health deterioration: Understanding disease pathways for personalized medicine
Artificial intelligence (AI) and machine learning (ML) methods are currently widely employed
in medicine and healthcare. A PubMed search returns more than 100,000 articles on these …
in medicine and healthcare. A PubMed search returns more than 100,000 articles on these …
Predicting the impact of treatments over time with uncertainty aware neural differential equations.
Predicting the impact of treatments from ob-servational data only still represents a major
challenge despite recent significant advances in time series modeling. Treatment …
challenge despite recent significant advances in time series modeling. Treatment …
Early diagnosis of multiple sclerosis using swept-source optical coherence tomography and convolutional neural networks trained with data augmentation
A López-Dorado, M Ortiz, M Satue, MJ Rodrigo… - Sensors, 2021 - mdpi.com
Background: The aim of this paper is to implement a system to facilitate the diagnosis of
multiple sclerosis (MS) in its initial stages. It does so using a convolutional neural network …
multiple sclerosis (MS) in its initial stages. It does so using a convolutional neural network …
Ensemble machine learning identifies genetic loci associated with future worsening of disability in people with multiple sclerosis
Limited studies have been conducted to identify and validate multiple sclerosis (MS) genetic
loci associated with disability progression. We aimed to identify MS genetic loci associated …
loci associated with disability progression. We aimed to identify MS genetic loci associated …
Combining clinical and genetic data to predict response to fingolimod treatment in relapsing remitting multiple sclerosis patients: a precision medicine approach
L Ferrè, F Clarelli, B Pignolet, E Mascia… - Journal of Personalized …, 2023 - mdpi.com
A personalized approach is strongly advocated for treatment selection in Multiple Sclerosis
patients due to the high number of available drugs. Machine learning methods proved to be …
patients due to the high number of available drugs. Machine learning methods proved to be …
Explainable machine learning on baseline MRI predicts multiple sclerosis trajectory descriptors
S Campanioni, C Veiga, JM Prieto-González… - Plos one, 2024 - journals.plos.org
Multiple sclerosis (MS) is a multifaceted neurological condition characterized by challenges
in timely diagnosis and personalized patient management. The application of Artificial …
in timely diagnosis and personalized patient management. The application of Artificial …
Retrospective cohort study to devise a treatment decision score predicting adverse 24-month radiological activity in early multiple sclerosis
Background: Multiple sclerosis (MS) is a chronic neuroinflammatory disease affecting about
2.8 million people worldwide. Disease course after the most common diagnoses of relapsing …
2.8 million people worldwide. Disease course after the most common diagnoses of relapsing …
Validation of a machine learning approach to estimate expanded disability status scale scores for multiple sclerosis
P Alves, E Green, M Leavy, H Friedler… - Multiple Sclerosis …, 2022 - journals.sagepub.com
Background Disability assessment using the Expanded Disability Status Scale (EDSS) is
important to inform treatment decisions and monitor the progression of multiple sclerosis …
important to inform treatment decisions and monitor the progression of multiple sclerosis …
Learning spatio-temporal model of disease progression with NeuralODEs from longitudinal volumetric data
Robust forecasting of the future anatomical changes inflicted by an ongoing disease is an
extremely challenging task that is out of grasp even for experienced healthcare …
extremely challenging task that is out of grasp even for experienced healthcare …