Results 101 to 110 of about 523,313 (224)

SCALE-BOSS-MR: Scalable Time Series Classification Using Multiple Symbolic Representations

Applied Sciences
Time-Series-Classification (TSC) is an important machine learning task for many branches of science. Symbolic representations of time series, especially Symbolic Fourier Approximation (SFA), have been proven very effective for this task, given their ...
Apostolos Glenis, George A. Vouros
doaj   +1 more source

Screening and epitope characterization of Nidogen‐2‐specific nanobodies

FEBS Open Bio, EarlyView.
Camel immunization and phage display were employed to generate high‐affinity VHH nanobodies against Nidogen‐2. After library construction, biopanning, ELISA screening, sequencing, and recombinant expression, selected nanobodies were purified and characterized, leading to the preliminary exploration of a nanobody‐based sandwich ELISA for specific ...
Jianchuan Wen, Qianqian Cui, Zhongyun Lan, Yingjun Wang, Shuaiying Zhao, Wenxuan Feng, Yunfeng Liu, Qiting Huang, Dongna Zhang, Jianfeng Xu   +9 more
wiley   +1 more source

Network Localization of Fatigue in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Fatigue is among the most common symptoms and one of the main factors determining the quality of life in multiple sclerosis (MS). However, the neurobiological mechanisms underlying fatigue are not fully understood. Here we studied lesion locations and their connections in individuals with MS, aiming to identify brain networks ...
Olli Likitalo, Jaakko Kungshamn, Albert Bellmunt‐Gil, Silvia Tommasin, Abhineet Ojha, Matias Viitala, Juho Aaltonen, Jyrki Lötjönen, Juha Koikkalainen, Pauli Ylikotila, Patrizia Pantano, Merja Soilu‐Hänninen, Juho Joutsa   +12 more
wiley   +1 more source

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah, Ioannis N. Petropoulos, Mark Stettner, Maryam Ferdousi, Uazman Alam, Nathan Efron, Ahmed Serag, Rayaz A. Malik   +7 more
wiley   +1 more source

Generalized ECG Heartbeat Classification Using Time-Series Transformers

IEEE Access
This research investigates Time-Series Transformer architectures for Electrocardiogram (ECG) heartbeat classification, particularly focusing on their generalization capabilities towards new patients and varying signal sampling rates, a critical challenge
Timo de Waele, Jaron Fontaine, Eli de Poorter, Adnan Shahid   +3 more
doaj   +1 more source

Prediction of Myasthenia Gravis Worsening: A Machine Learning Algorithm Using Wearables and Patient‐Reported Measures

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Myasthenia gravis (MG) is a rare disorder characterized by fluctuating muscle weakness with potential life‐threatening crises. Timely interventions may be delayed by limited access to care and fragmented documentation. Our objective was to develop predictive algorithms for MG deterioration using multimodal telemedicine data ...
Maike Stein, Haoqi Sun, Sophie Lehnerer, Lea Gerischer, Maximilian Mönch, Christian Meisel, Andreas Meisel, Pushpa Narayanaswami   +7 more
wiley   +1 more source

AdaPDTW: An Efficient Abstract-Adaptive Piecewise Dynamic Time Warping for Time Series Classification

IEEE Access
Dynamic Time Warping (DTW) offers precise similarity measure but suffers from high computational cost. To address this issue, we propose an abstract-adaptive PAR-DTW, which computes DTW in a low-dimensional piecewise abstract representation (PAR) space ...
Qinglin Cai, Leiying Chen, Jian Shao, Ling Chen   +3 more
doaj   +1 more source

Chronological and Spatial Distribution of Skeletal Muscle Fat Replacement in FHL1‐Related Myopathies

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Variants in the FHL1 gene cause FHL1‐related myopathies (FHL1‐RMs), a group of neuromuscular disorders with diverse clinical presentations. This study aimed to comprehensively characterize the spatial and temporal patterns of skeletal muscle fat replacement throughout the whole body in FHL1‐RMs, to examine disease progression over ...
Rui Shimazaki, Satoru Noguchi, Hotake Takizawa, Yasushi Oya, Yuji Takahashi, Hirofumi Komaki, Hajime Arahata, Shinichiro Hayashi, Ichizo Nishino   +8 more
wiley   +1 more source

Age‐Related Characteristics of SYT1‐Associated Neurodevelopmental Disorder

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives We describe the clinical manifestations and developmental abilities of individuals with SYT1‐associated neurodevelopmental disorder (Baker‐Gordon syndrome) from infancy to adulthood. We further describe the neuroradiological and electrophysiological characteristics of the condition at different ages, and explore the associations ...
Sam G. Norwitz, Josefine Eck, Joel S. Winston, Kate Baker   +3 more
wiley   +1 more source

Time-series visual representations for sleep stages classification.

PLoS ONE
Polysomnography is the standard method for sleep stage classification; however, it is costly and requires controlled environments, which can disrupt natural sleep patterns.
Rebeca Padovani Ederli, Didier A Vega-Oliveros, Aurea Soriano-Vargas, Anderson Rocha, Zanoni Dias   +4 more
doaj   +1 more source