Results 141 to 150 of about 187,533 (264)
Metric Learning for Structured Data
Distance measures form a backbone of machine learning and information retrieval in many application fields such as computer vision, natural language processing, and biology. However, general-purpose distances may fail to capture semantic particularities of a domain, leading to wrong inferences downstream. Motivated by such failures, the field of metric
openaire +2 more sources
Upper Cervical Cord Area as a Biomarker of Conversion to Secondary Progressive Multiple Sclerosis
ABSTRACT Objective This study assessed whether upper cervical cord area (UCCA) measured on routine brain MRI can serve as a biomarker of conversion to SPMS. Methods This is a single‐center retrospective cohort study of RRMS patients with cross‐sectional and longitudinal analyses of clinical and MRI data. Future SPMS converters were matched by age, sex,
Nabil K. El Ayoubi +8 more
wiley +1 more source
Patient Reidentification from Chest Radiographs: An Interpretable Deep Metric Learning Approach and Its Applications. [PDF]
Macpherson MS +4 more
europepmc +1 more source
ABSTRACT Objectives Focal cortical dysplasia (FCD) is the most common etiology of drug‐resistant epilepsy in children. Focal to bilateral tonic–clonic seizures (FBTCS) mark a high risk of drug‐resistant epilepsy and involve thalamocortical circuitry in their generation and propagation.
Hua Xie +8 more
wiley +1 more source
Deep Metric Learning Using Negative Sampling Probability Annealing. [PDF]
Kertész G.
europepmc +1 more source
Digital Cognitive Testing in Mitochondrial Disease: Validity and Challenges for Clinical Trial Use
ABSTRACT Background Primary mitochondrial disease is a group of genetic disorders caused by pathogenic variants in nuclear or mitochondrial DNA, often resulting in progressive neurodegeneration and cognitive decline. Current management is primarily supportive, though recent research offers hope for disease‐modifying treatments in the future.
Oksana Pogoryelova +9 more
wiley +1 more source
Residual metric learning with class-specific consistency for multiclass classification. [PDF]
Hu K, Ma J.
europepmc +1 more source
Contrastive Metric Learning for Lithium Super-ionic Conductor Screening. [PDF]
Zhang B, Wang S, Gao F.
europepmc +1 more source
ABSTRACT Objective To determine whether myelin‐sensitive quantitative MRI reveals microstructural abnormalities in normal‐appearing cortex (NACtx) in myelin oligodendrocyte glycoprotein antibody–associated disease (MOGAD), indicating that conventional MRI underestimates remission residual cortical injury.
Valentina Camera +20 more
wiley +1 more source

