Publications by authors named "J Pruvo"
In MRI studies, the aggregation of imaging data from multiple acquisition sites enhances sample size but may introduce site-related variabilities that hinder consistency in subsequent analyses. Deep learning methods for image translation have emerged as a solution for harmonizing MR images across sites. In this study, we introduce IGUANe (Image Generation with Unified Adversarial Networks), an original 3D model that leverages the strengths of domain translation and straightforward application of style transfer methods for multicenter brain MR image harmonization.
View Article and Find Full Text PDFPurpose To assess the performance of a local open-source large language model (LLM) in various information extraction tasks from real-life emergency brain MRI reports. Materials and Methods All consecutive emergency brain MRI reports written in 2022 from a French quaternary center were retrospectively reviewed. Two radiologists identified MRI scans that were performed in the emergency department for headaches.
View Article and Find Full Text PDFArticle Synopsis
- - Catatonia is a psychomotor syndrome with various motor and behavioral symptoms, and benzodiazepines are the primary treatment, working for about 70% of patients; however, the reasons for resistance in some cases are still unclear.
- - Researchers developed machine learning models using clinical evaluations and brain MRI data from 65 catatonic patients to predict responses to benzodiazepine treatment, classifying them into responders and non-responders.
- - The models showed improved accuracy when incorporating neuroimaging data, identifying key factors—such as the duration of the syndrome and brain volume in specific areas—that help predict which patients are likely to not respond to treatment.