Results 51 to 60 of about 44,296 (265)

Advancing Age Modulates Associations Between Cognitive Impairment and Brain Volumes in Early MS

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Introduction Cognitive impairment is common in multiple sclerosis (MS), but manifestations following the first demyelinating event are relatively unexplored. We investigated cross‐sectional associations between magnetic resonance imaging (MRI)–derived brain volumes and the presence of cognitive impairment outcomes five years after the first ...
Piriyankan Ananthavarathan, Marco Pitteri, Michael Foster, Sara Collorone, Sara Salama, Elisa Colato, Ferran Prados, Baris Kanber, Marios Yiannakas, Claudia A. M. Gandini Wheeler‐Kingshott, Indran Davagnanam, Frederik Barkhof, Declan Chard, Olga Ciccarelli, Ahmed Toosy   +14 more
wiley   +1 more source

Advancements in Semi-Supervised Deep Learning for Brain Tumor Segmentation in MRI: A Literature Review

AI
For automatic tumor segmentation in magnetic resonance imaging (MRI), deep learning offers very powerful technical support with significant results. However, the success of supervised learning is strongly dependent on the quantity and accuracy of labeled
Chengcheng Jin, Theam Foo Ng, Haidi Ibrahim   +2 more
doaj   +1 more source

On Ensemble SSL Algorithms for Credit Scoring Problem

Informatics, 2018
Credit scoring is generally recognized as one of the most significant operational research techniques used in banking and finance, aiming to identify whether a credit consumer belongs to either a legitimate or a suspicious customer group.
Ioannis E. Livieris, Niki Kiriakidou, Andreas Kanavos, Vassilis Tampakas, Panagiotis Pintelas   +4 more
doaj   +1 more source

AI-Assisted Cotton Grading: Active and Semi-Supervised Learning to Reduce the Image-Labelling Burden

Sensors, 2023
The assessment of food and industrial crops during harvesting is important to determine the quality and downstream processing requirements, which in turn affect their market value. While machine learning models have been developed for this purpose, their
Oliver J. Fisher, Ahmed Rady, Aly A. A. El-Banna, Haitham H. Emaish, Nicholas J. Watson   +4 more
doaj   +1 more source

Comparing the Effect of Semi‐Immersive Virtual Reality, Computerized Cognitive Training, and Traditional Rehabilitation on Cognitive Function in Multiple Sclerosis: A Randomized Clinical Trial

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio, Desiree Latella, Lilla Bonanno, Paulo Cezar Rocha dos Santos, Marcos Maldonado‐Díaz, Meir Plotnik, Rosaria De Luca, Angelo Quartarone, Rocco Salvatore Calabrò   +8 more
wiley   +1 more source

Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif, Diane Demailly, Gabriella A. Horvàth, Juan Dario Ortigoza Escobar, Nathalie Dorison, Mayté Castro Jiménez, Cécile A. Hubsch, Thomas Wirth, Gun‐Marie Hariz, Sophie Huby, Morgan Dornadic, Zohra Souei, Muhammad Mushhood Ur Rehman, Simone Hemm, Mehdi Boulaymen, Eduardo M. Moraud, Jocelyne Bloch, Xavier Vasques   +17 more
wiley   +1 more source

SEMI-SUPERVISED MARGINAL FISHER ANALYSIS FOR HYPERSPECTRAL IMAGE CLASSIFICATION [PDF]

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012
The problem of learning with both labeled and unlabeled examples arises frequently in Hyperspectral image (HSI) classification. While marginal Fisher analysis is a supervised method, which cannot be directly applied for Semi-supervised classification ...
H. Huang, J. Liu, Y. Pan
doaj   +1 more source

Temporal Interference Stimulation of Centromedian‐Parafascicular Complex in Disorders of Consciousness: A Pilot Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Treatment of disorders of consciousness (DoC) remains a major clinical challenge, and noninvasive, targeted modulation of deep brain structures has emerged as a promising therapeutic strategy. We aimed to evaluate the feasibility/safety and preliminary effects of thalamic temporal interference stimulation (TIS) targeting centromedian‐
Gengyao Hu, Changgeng Song, Dianwei Wu, Xiaoqian Niu, Jianmin Hao, Lijuan Liu, Xiaogang Kang, Wen Jiang   +7 more
wiley   +1 more source

Geostatistical semi-supervised learning for spatial prediction

Artificial Intelligence in Geosciences, 2022
Geoscientists are increasingly tasked with spatially predicting a target variable in the presence of auxiliary information using supervised machine learning algorithms.
Francky Fouedjio, Hassan Talebi
doaj   +1 more source

In-Context Semi-Supervised Learning

CoRR
There has been significant recent interest in understanding the capacity of Transformers for in-context learning (ICL), yet most theory focuses on supervised settings with explicitly labeled pairs. In practice, Transformers often perform well even when labels are sparse or absent, suggesting crucial structure within unlabeled contextual demonstrations.
Jiashuo Fan, Paul Rosu, Aaron T. Wang, Michael Li, Lawrence Carin, Xiang Cheng   +5 more
openaire   +2 more sources