Results 101 to 110 of about 252,636 (309)
, 2023 Illustration of how data augmentation algorithm works. A, 25 intact random images from the dataset; B, C, and D, random data augmentations applied to that same 25 images, which would then feed to the model.
Ava Akhavan Malayeri (15295175) +3 more
core +1 more source
A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi +17 more
wiley +1 more source
Data Augmentation through Generative Models [PDF]
openIn recent years, semantic segmentation has emerged as a critical task in computer vision, vital for applications ranging from autonomous driving to medical image analysis.
TOFFANIN, MATTIA
core
Data Augmentation: Enhancing Named Entity Recognition Performance on Swedish Medical Texts [PDF]
, 2023 Named Entity Recognition (NER) refers to the task of locating relevant information within text sequences. Within the medical domain, it can benefit applications such as de-identifying patient records or extracting valuable data for other downstream tasks.
Rosvall, Lucas, Paasonen, Niklas
core
Annals of Clinical and Translational Neurology, EarlyView.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
Handwriting Recognition using Deep Learning with Effective Data Augmentation Techniques
, 2021 Machine learning techniques have been successfully used in deciphering handwritten text. Deep learning has made further improvements in this regard. However, they require substantial amounts of training data.
Lidzhade, Ipfi, Brown, Dane L
core
Data Augmentation Techniques for fMRI Data: A Technical Survey
IEEE AccessThe application of machine learning to fMRI data classification, prediction, and analysis tasks has experienced rapid growth in recent years. However, its implementation has been limited by the relatively small size of labeled fMRI datasets.
Valentina Sanchez +3 more
doaj +1 more source
Long‐Term Neurologic Exam Findings in People Diagnosed and Treated During Acute HIV Infection
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Evaluate clinical and laboratory correlates of abnormal neurologic exam findings after acute HIV infection (AHI). Methods Participants from the RV254/SEARCH 010 cohort in Bangkok underwent standardized neurologic examinations at Weeks 0 (AHI), 12, 96, and 288 following antiretroviral therapy (ART).
Kathryn B. Holroyd +118 more
wiley +1 more source
Data augmentation for semantic segmentation in colonoscopy examinations.
, 2022 non
CUZA, DANIELA
core
Cognitive Behavioral Therapy for Youth With Childhood‐Onset Lupus: A Randomized Clinical Trial
Arthritis Care &Research, EarlyView.Objective Our objective was to determine the feasibility and acceptability of the Treatment and Education Approach for Childhood‐Onset Lupus (TEACH), a six‐session cognitive behavioral intervention addressing depressive, fatigue, and pain symptoms, delivered remotely to individual youth with lupus by a trained interventionist.
Natoshia R. Cunningham +29 more
wiley +1 more source