PIP: Pictorial Interpretable Prototype Learning for Time Series Classification. [PDF]
Ghods A, Cook DJ.
europepmc +1 more source
Epilepsy‐Associated Variants of a Single SCN1A Codon Exhibit Divergent Functional Properties
ABSTRACT Objective Pathogenic variants in SCN1A, which encodes the voltage‐gated sodium channel NaV1.1, are associated with multiple epilepsy syndromes exhibiting a range of clinical severity. SCN1A variants are reported in different syndromes, including Dravet syndrome, which is associated with loss‐of‐function, whereas neonatal/infantile‐onset ...
Lanie N. Liebovitz +3 more
wiley +1 more source
Decoupled Early Time Series Classification Using Varied-Length Feature Augmentation and Gradient Projection Technique. [PDF]
Chen H +5 more
europepmc +1 more source
A Systematic Review and Meta‐Analysis of the Recurrence of Autoimmune Encephalitis
ABSTRACT Objective Autoimmune encephalitis (AE) is a disease with a potential for recurrence, and patients receive immunotherapy to prevent it. However, there is no consensus on the duration of immunotherapy. This study aimed to determine the recurrence rate and identify the risk factors for AE to provide guidance on the duration of immunotherapy ...
Shangkai Bai +5 more
wiley +1 more source
A Comprehensive Explanation Framework for Biomedical Time Series Classification. [PDF]
Ivaturi P +5 more
europepmc +1 more source
CSF Monoamine Metabolites and Cognitive Trajectory in Early Parkinson's Disease
ABSTRACT Background Imaging and postmortem studies indicate that abnormalities in monoaminergic neurotransmission contribute to cognitive impairment in Parkinson's disease (PD). However, it remains uncertain if cerebrospinal fluid (CSF) monoamine metabolites can serve as biomarkers of cognitive decline in early PD.
Jing‐Yu Shao +7 more
wiley +1 more source
EffiShapeFormer: Shapelet-Based Sensor Time Series Classification with Dual Filtering and Convolutional-Inverted Attention. [PDF]
Bao J +12 more
europepmc +1 more source
Predicting the outcome for COVID-19 patients by applying time series classification to electronic health records. [PDF]
Rodrigues DS +11 more
europepmc +1 more source
One-Class Time Series Classification
This thesis contributes to the state of the art of time series classification and machine learning by investigating three novel data-driven representations for time series in the context of one-class classification. The one-class assumption is useful for all classification problems where only data of a single class is available for training a ...
openaire +1 more source
Objective We evaluated the ability of the Renal Activity Index for Lupus (RAIL) to discriminate active lupus nephritis (LN) in adult patients with active systemic lupus erythematosus (SLE) and differentiate LN treatment response. Methods Urine samples from adults with biopsy‐proven active class III and IV LN from TULIP‐LN (active LN group ...
Hermine I. Brunner +12 more
wiley +1 more source

