output
20162025
most citedConditional canonical correlation estimation based on covariates with random forests

28 citations

18 papers

q-bio.TO2025★ 1 cited

Segmentation of spinal rootlets across MRI contrasts with RootletSeg

Katerina Krejci, Jiri Chmelik, Sandrine Bedard +5

Purpose: To develop a deep learning method for the automatic segmentation of spinal nerve rootlets on various MRI scans. Material and Methods: This retrospective study included MRI…

eess.IV2024

Unpaired Modality Translation for Pseudo Labeling of Histology Images

Arthur Boschet, Armand Collin, Nishka Katoch +1

The segmentation of histological images is critical for various biomedical applications, yet the lack of annotated data presents a significant challenge. We propose a microscopy ps…

cs.LG2024★ 9 cited

Development and Comparative Analysis of Machine Learning Models for Hypoxemia Severity Triage in CBRNE Emergency Scenarios Using Physiological and Demographic Data from Medical-Grade Devices

Santino Nanini, Mariem Abid, Yassir Mamouni +3

This paper presents the development of machine learning (ML) models to predict hypoxemia severity during emergency triage, especially in Chemical, Biological, Radiological, Nuclear…

cs.CV2024★ 3 cited

SCIsegV2: A Universal Tool for Segmentation of Intramedullary Lesions in Spinal Cord Injury

Enamundram Naga Karthik, Jan Valošek, Lynn Farner +10

Spinal cord injury (SCI) is a devastating incidence leading to permanent paralysis and loss of sensory-motor functions potentially resulting in the formation of lesions within the…

cs.CV2024★ 7 cited

Harmonizing Flows: Leveraging normalizing flows for unsupervised and source-free MRI harmonization

Farzad Beizaee, Gregory A. Lodygensky, Chris L. Adamson +5

Lack of standardization and various intrinsic parameters for magnetic resonance (MR) image acquisition results in heterogeneous images across different sites and devices, which adv…

cs.CL2024★ 12 cited

The Impact of LoRA Adapters on LLMs for Clinical Text Classification Under Computational and Data Constraints

Thanh-Dung Le, Ti Ti Nguyen, Vu Nguyen Ha +3

Fine-tuning Large Language Models (LLMs) for clinical Natural Language Processing (NLP) poses significant challenges due to domain gap, limited data, and stringent hardware constra…