Results 131 to 140 of about 1,500,141 (319)

An MRI assessment of mechanisms underlying lesion growth and shrinkage in multiple sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
By applying the tensor model, we analysed lesion orientation and the directionality of lesion expansion/contraction in multiple sclerosis. Each lesion is summarized as an ellipsoid, and the tensor model is applied to calculate lesion anisotropy. From the top to the bottom white matter atlas, surface‐in gradient segmentation and venous atlas used in the
Ermelinda De Meo, Ferran Prados Carrasco, J. William L. Brown, Alasdair J. Coles, Nick G. Cunniffe, Amy E. Jolly, Baris Kanber, Rebecca Samson, Frederik Barkhof, Declan Chard   +9 more
wiley   +1 more source

Investigating LLMs in Clinical Triage: Promising Capabilities, Persistent Intersectional Biases [PDF]

arXiv
Large Language Models (LLMs) have shown promise in clinical decision support, yet their application to triage remains underexplored. We systematically investigate the capabilities of LLMs in emergency department triage through two key dimensions: (1) robustness to distribution shifts and missing data, and (2) counterfactual analysis of intersectional ...
arxiv  

THE DIFFERENTIATION AND ABERRATIONS OF SEX CHARACTERISTICS [PDF]

BMJ, 1935
openaire   +3 more sources

If it does not help, it might hurt: Pharmacodynamics of a second IVIg course in Guillain–Barré syndrome

Annals of Clinical and Translational Neurology, EarlyView.
Abstract Objectives Intravenous immunoglobulin (IVIg) is an effective treatment for Guillain–Barré syndrome (GBS), but recovery varies between patients. This study aims to evaluate the pharmacokinetics (PK) and pharmacodynamics (PD) of a single and a second IVIg dose (SID) in patients with GBS.
Sander J. van Tilburg, Ruth Huizinga, Krista Kuitwaard, Sebastiaan D.T. Sassen, Christa Walgaard, Pieter A. van Doorn, Bart C. Jacobs, Birgit C.P Koch   +7 more
wiley   +1 more source

HLA-DRB1* genotypes in Greek rheumatoid arthritis patients: association with disease characteristics, sex and age at onset [PDF]

, 1997
C Stavropoulos, M. Spyropoulou, Y. Koumantaki, I. Kappou, P. V. Kaklamanis, Athena Linos, Ernestini Giziaki, E. Kaklamani   +7 more
openalex   +1 more source

Twelve‐month change in quantitative MRI calf muscle fat fraction in CMT1A predicts clinical change over 4 years

Annals of Clinical and Translational Neurology, EarlyView.
Abstract Objective We measured clinical and quantitative MRI outcome measures in CMT1A to assess long‐term responsiveness, establish longitudinal validity and assess MRI as a bridging biomarker. Methods Twenty patients with CMT1A and 20 matched controls underwent MRI, myometry and clinical assessments up to four times over mean 4‐year follow‐up ...
Matthew R. B. Evans, Hamza A. Salhab, Christopher D. J. Sinclair, Sachit Shah, Michael G. Hanna, Tarek A. Yousry, John S. Thornton, Jasper M. Morrow, Mary M. Reilly   +8 more
wiley   +1 more source

Detecting Unforeseen Data Properties with Diffusion Autoencoder Embeddings using Spine MRI data [PDF]

arXiv
Deep learning has made significant strides in medical imaging, leveraging the use of large datasets to improve diagnostics and prognostics. However, large datasets often come with inherent errors through subject selection and acquisition. In this paper, we investigate the use of Diffusion Autoencoder (DAE) embeddings for uncovering and understanding ...
arxiv  

Puberty begins with a characteristic subcutaneous body fat mass in each sex [PDF]

, 2000
Bárbara Vizmanos, C Martí‐Henneberg
openalex   +1 more source

Clinical impact and safety of brain biopsy in unexplained central nervous system disorders: a real‐world cohort study

Annals of Clinical and Translational Neurology, EarlyView.
Abstract Objective A substantial part of central nervous system (CNS) disorders remains unexplained, despite various new and minimally invasive diagnostic techniques. Within this rapidly developing diagnostic field, the precise role of brain biopsy is unknown.
Robin W. van Steenhoven, Saan Salih, Juna M. de Vries, Ide Smets, Rob M. Verdijk, Mayke Gardeniers, Jeroen Kerstens, Juliette Brenner, Yvette S. Crijnen, Marjolein Geurts, Jacoline E. C. Bromberg, Corine H. GeurtsvanKessel, Peter A. E. Sillevis Smitt, Rutger K. Balvers, Maarten J. Titulaer   +14 more
wiley   +1 more source

Quantifying the Impact of Population Shift Across Age and Sex for Abdominal Organ Segmentation [PDF]

arXiv
Deep learning-based medical image segmentation has seen tremendous progress over the last decade, but there is still relatively little transfer into clinical practice. One of the main barriers is the challenge of domain generalisation, which requires segmentation models to maintain high performance across a wide distribution of image data.
arxiv