Results 101 to 110 of about 8,510,788 (298)

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, Tyler Hamby, Carlo Sacdalan, Somchai Sriplienchan, Pathariya Promensa, Luxenaree Poonpitak, Netsiri Dumrongpisutikul, Eugène Kroon, Sandhya Vasan, Robert Paul, Ferron O'Campo, Lydie Trautmann, Phillip Chan, Serena Spudich, on behalf of the RV254/SEARCH 010 Study Team, Julie Ake, Sandhya Vasan, Lydie Trautmann, Merlin Robb, Trevor Crowell, Donn Colby, Diane Bolton, Shelly Krebs, Leigh Ann Eller, Morgane Rolland, Rasmi Thomas, Dominic Paquin Proulx, Suteeraporn Pinyakorn, Tyler Hamby, Mark de Souza, Ellen Turk, Amber Moodley, Gerald Quarles, Jintanat Ananworanich, Denise Hsu, Victoria Polonis, Nelson Michael, Sheila Peel, COL Eric Garges, Alexandra Schuetz, Siriwat Akapirat, Bessara Nantapinit, Pornsuk Visudhiphan, Saowanit Getchalarat, Nampueng Churikanont, Sangsulee Thamakaison, Somchai Sriplienchan, Carlo Sacdalan, Pathariya Promsena, Luxe‐naree Poonpitak, Eugene Kroon, Nitiya Chomchey, Jintana Intasan, Varaporn Pothipala, Ferron Ocampo, Nittaya Phanuphak, Nipat Teeratakulpisan, Yuwaree Pichitchok, Anchalee Avihingsanon, Opass Putcharoen, Kiat Ruxrungtham, Thanyawee Puthanakit, Sopark Manasnayakorn, Phandee Watanaboonyongcharoen, Rungsun Rerknimitr, Irini Sereti, Daniel Douek, Eli Bortiz, Frank Maldarelli, Mary Kearney, Serena Spudich, Phillip Chan, Lishomwa Ndhlovu, Guinevere Li, Michael Corley, Victor Valcour, Peter Hunt, Jacob Estes, Afam Okoye, Jeff Lifson, Claire Deleage, Nicolas Chomont, Andres Finzi, Lyle McKinnon, Henrik Zetterberg, Robert Siliciano, Robert Paul, Julie Mannarino, Jonathan Li, John Mellors, Josh Cytkor, Dan Barouch, Michael Seaman, Boris Juelg, Alex Shalek, Timothy Schacker, Ashley Haase, Mario Stevenson, Wenjun Li, Arthur Kim, Sharon Lewin, Adam Carrico, Susana Valente, Fred Hutchinson, Josh Schiffer, Guido Ferrari, Beau Ances, Alberto Bosque, Katharine Bar, Killian Pohl, David Ho, Yaoxing Huang, Michael Busch, Mohamed Abdel‐Mohsen, Johanna Gostner, Brian Agan, Fatah Kashanchi, Greg Laird, Kathryn Holroyd   +118 more
wiley   +1 more source

Source-Free Domain Adaptive Semantic Segmentation of Remote Sensing Images With Diffusion-Guided Label Enrichment

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Source-free domain adaptation for remote sensing semantic segmentation is highly challenging due to the inaccessibility of source data and the absence of target annotations during adaptation.
Wenjie Liu, Hongmin Liu, Lixin Zhang, Bin Fan   +3 more
doaj   +1 more source

The Price of Precision: A Critical Review of Molecular Diagnostics in Glioma, From Guidelines to Global Disparities

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Gliomas have undergone a profound redefinition over the past decade, transitioning from morphology‐based entities to biologically coherent diseases defined by molecular alterations. The 2021 WHO Classification of Tumors of the Central Nervous System and its 2022 update formalize this shift, establishing integrated diagnosis as the global ...
Maria Guarnaccia, Sebastiano Cavallaro
wiley   +1 more source

FedMSIS-BiDir: Federated Self-Training With Temporal Pseudo-Label Refinement for Object Detection

IEEE Access
Federated learning (FL) enables distributed model training without centralizing raw data, but it often suffers from scarce labeled annotations on client devices.
Shoaib Sajid, Zafar Aziz, Shimaa Abdelnabi Abdel Hakeem, Hyungwon Kim   +3 more
doaj   +1 more source

A Unified Contrastive Loss for Self-training

Self-training methods have proven to be effective in exploiting abundant unlabeled data in semi-supervised learning, particularly when labeled data is scarce. While many of these approaches rely on a cross-entropy loss function (CE), recent advances have shown that the supervised contrastive loss function (SupCon) can be more effective.
Aurélien Gauffre, Julien Horvat, Massih-Reza Amini   +2 more
openaire   +4 more sources

Self-Training the Neurochaos Learning Algorithm

Chaos Theory and Applications
In numerous practical applications, acquiring substantial quantities of labelled data is challenging and expensive, but unlabelled data is readily accessible. Conventional supervised learning methods frequently underperform in scenarios characterised by little labelled data or imbalanced datasets. This study introduces a hybrid semi-supervised learning
Anusree M, Akhila Henry, Pramod Nair
openaire   +2 more sources

Are self-employment training programs effective? Evidence from Project GATE [PDF]

In 2002, the U.S. Department of Labor and the Small Business Administration implemented Project GATE, an experimental demonstration program designed to provide free self-employment assistance to individuals interested in starting their own business. This
Benus, Jacob, Michaelides, Marios
core  

Impact of Age on the Diagnostic Yield of Routine EEG in People With Childhood or Juvenile Absence Epilepsy: A Cross‐Sectional Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background We aimed to identify the proportion of individuals with a confirmed diagnosis of childhood absence epilepsy (CAE) or juvenile absence epilepsy (JAE) who show a negative routine EEG (rEEG), and to determine the main factors associated with this finding.
Francesco Fortunato, Alessia Giugno, Miriam Sturniolo, Enrico Fratto, Pio Zoleo, Francesca Felicia Operto, Ilaria Sammarra, Antonio Gambardella   +7 more
wiley   +1 more source

Reserves, Injury Severity, and Outcomes in Traumatic Brain Injury: A CENTER‐TBI Observational Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Reserve refers to the brain's ability to maintain function after an injury and strongly relates to traumatic brain injury (TBI) outcomes. This study examined (1) whether associations between pre‐injury reserve proxies and outcomes differed across injury severity categories, and (2) whether the impact of injury severity varied across ...
Natascha Ekdahl, Marika C. Möller, Lindsay Wilson, Anne Vik, Toril Skandsen, Jonas Stenberg, CENTER‐TBI participants and investigators   +6 more
wiley   +1 more source

Calibrated Adaptive Teacher for Domain-Adaptive Intelligent Fault Diagnosis

Sensors
Intelligent fault diagnosis (IFD) based on deep learning can achieve high accuracy from raw condition monitoring signals. However, models usually perform well on the training distribution only, and experience severe performance drops when applied to a ...
Florent Forest, Olga Fink
doaj   +1 more source