Results 121 to 130 of about 1,025,950 (315)

Baseline Regional Cholinergic Denervation Predicts Cognitive Trajectories in Moderate Parkinson Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Cognitive decline is a disabling and variable feature of Parkinson disease (PD). While cholinergic system degeneration is linked to cognitive impairments in PD, most prior research reported cross‐sectional associations. We aimed to fill this gap by investigating whether baseline regional cerebral vesicular acetylcholine transporter ...
Taylor Brown, Giulia Carli, Prabesh Kanel, Stiven Roytman, Jaimie Barr, Nicolaas I. Bohnen, Roger L. Albin   +6 more
wiley   +1 more source

Energy-efficient analog-domain aggregator circuit for RRAM-based neural network accelerators

Frontiers in Electronics
Recently, there has been notable progress in the advancement of RRAM-based Compute-In-Memory (CIM) architectures, showing promise in accelerating neural networks with remarkable energy efficiency and parallelism.
Khaled Humood, Yihan Pan, Shiwei Wang, Alexander Serb, Themis Prodromakis   +4 more
doaj   +1 more source

FDG‐PET Associations With Disease Severity and Outcomes in NMDA‐Receptor IgG Autoimmune Encephalitis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Patients with N‐methyl‐D‐aspartate (NMDA) receptor‐immunoglobulin G (IgG) autoimmune encephalitis (NMDAR‐IgG AE) demonstrate occipital lobe hypometabolism on baseline brain fluorodeoxyglucose‐positron emission tomography (bFDG‐PET).
Jonathan K. Lee, Jeffrey Lambe, Scott Johnson, Akua Abrah, Jennifer Bullen, Jeffrey A. Cohen, Tatchaporn Ongphichetmetha, Amy Kunchok   +7 more
wiley   +1 more source

Temporal correlation detection using computational phase-change memory

Nature Communications, 2017
New computing paradigms, such as in-memory computing, are expected to overcome the limitations of conventional computing approaches. Sebastian et al. report a large-scale demonstration of computational phase change memory (PCM) by performing high-level ...
Abu Sebastian, Tomas Tuma, Nikolaos Papandreou, Manuel Le Gallo, Lukas Kull, Thomas Parnell, Evangelos Eleftheriou   +6 more
doaj   +1 more source

Non-volatile in-memory computing [PDF]

, 2019
The analysis of big-data at exa-scale (1018 bytes or flops) has called for an urgent need to re-examine the existing hardware platform that can support intensive data-oriented computing. A big-data-driven application requires huge bandwidth and yet able to ensure low-power density.
openaire   +2 more sources

Monocyte LOXHD1 and RHOB Expression Predictive of Progressive Systemic Sclerosis–Associated Interstitial Lung Disease

Arthritis Care &Research, EarlyView.
Objective A leading cause of death among patients with scleroderma (SSc), interstitial lung disease (ILD) remains challenging to prognosticate. The discovery of biomarkers that accurately determine which patients would benefit from close monitoring and aggressive therapy would be an essential clinical tool.
Cristina M. Padilla, Robert Lafyatis, Kevin F. Gibson, Christina Morse, Eleanor Valenzi, Xiaoping Chen, Xiaoyun Li, Yanwu Zhao, Yongseok Park, Dana Ascherman, Jonathan Minden, Robyn Domsic, Yingze Zhang, Daniel J. Kass   +13 more
wiley   +1 more source

A review on selective in-memory computing processors: Potential alternative to AI-driven applications

Results in Engineering
In-memory computing (IMC) is a paradigm-shifting approach to data processing that eliminates the sluggishness of transferring data between memory and processing units. By integrating computation directly within the memory, IMC accelerates performance for
Mohith V, Sakthivel R
doaj   +1 more source

Testing a Personalized Approach to Chronic Low Back Pain: A Randomized Controlled Trial in Older Veterans

Arthritis Care &Research, EarlyView.
Objective We aimed to test the efficacy of personalized treatment of older veterans with chronic low back pain (CLBP) delivered by Aging Back Clinics (ABCs) as compared with usual care (UC). Methods Two hundred ninety‐nine veterans aged 65 to 89 with CLBP from three Veterans Affairs (VA) medical centers underwent baseline testing, randomization to ABC ...
Debra K. Weiner, Angela Gentili, Meika A. Fang, Edward Garay, Laura Lawson, Lenore Joseph, Cathy C. Lee, Michelle I. Rossi, Beverly Thorn, Subashan Perera   +9 more
wiley   +1 more source

Pharmacokinetics, Pharmacodynamics, and Safety of Subcutaneous Belimumab in Pediatric Patients With Systemic Lupus Erythematosus: A Multicenter, Open‐Label Trial

Arthritis Care &Research, EarlyView.
Objective This study aimed to characterize the pharmacokinetics, pharmacodynamics, safety, and exploratory efficacy of subcutaneous belimumab in pediatric patients with active systemic lupus erythematosus (SLE) receiving standard therapy. Methods This single‐arm, multicenter, open‐label trial (GSK study 200908; ClinicalTrials.gov identifier ...
Hermine I. Brunner, Jordi Antón, Inmaculada Calvo‐Penadés, Richard Dimelow, Gerd Horneff, Sylvia Kamphuis, Rebecca Marino, Andre van Maurik, Kirsten Minden, Masaaki Mori, Josephine Ocran‐Appiah, Christel Wilkinson, Yuichi Yamasaki, Deepak Assudani, for the Pediatric Rheumatology Collaborative Study Group (PRCSG) and Paediatric Rheumatology International Trials Organisation (PRINTO) Network investigators   +14 more
wiley   +1 more source

Kernel approximation using analogue in-memory computing

Nature Machine Intelligence
Kernel functions are vital ingredients of several machine learning algorithms, but often incur significant memory and computational costs. We introduce an approach to kernel approximation in machine learning algorithms suitable for mixed-signal Analog In-Memory Computing (AIMC) architectures.
Julian Büchel, Giacomo Camposampiero, Athanasios Vasilopoulos, Corey Lammie, Manuel Le Gallo, Abbas Rahimi, Abu Sebastian   +6 more
openaire   +2 more sources