Results 261 to 270 of about 667,864 (326)

Signal and Contrast Optimization With Predicted Excitations (SCOPE) for Accelerating Large FOV Body Imaging at UHF

open access: yesMagnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose Large FOV turbo‐spin‐echo (TSE) imaging at ultra‐high field (UHF) remains challenging due to B1+ inhomogeneity and peak specific absorption rate (pSAR) limitations. This work presents a new time‐interleaved acquisition of modes (TIAMO) framework called SCOPE (Signal and Contrast Optimization with Predicted Excitations), which overcomes
Tobey D. Haluptzok   +2 more
wiley   +1 more source

BarkVisionAI: Novel dataset for rapid tree species identification. [PDF]

open access: yesSci Data
Chhatre A   +4 more
europepmc   +1 more source

Opening the Black Box of Nonprofit Reputation and Volunteer Attraction With Supervised Machine Learning

open access: yesNonprofit Management and Leadership, EarlyView.
ABSTRACT With the aim to explore the potential of machine learning for nonprofit research, this article contrasts traditional linear regression with four contemporary supervised machine learning approaches. Concretely, we predict (1) reputation ratings and (2) the total number of volunteers for 4021 non‐profit organizations in the U.S.
Moritz Schmid   +2 more
wiley   +1 more source

Leveraging large language models for structured information extraction from pathology reports. [PDF]

open access: yesJ Pathol Inform
Balasubramanian JB   +6 more
europepmc   +1 more source

Use of Naltrexone–Bupropion in Persons With Overweight/Obesity and Symptoms of Depression: A Pooled Analysis

open access: yesObesity, EarlyView.
ABSTRACT Objective The present study examined the safety and efficacy of the fixed‐dose, extended‐release combination of naltrexone and bupropion (NB‐ER) in individuals with overweight/obesity and mild to moderate symptoms of depression. Methods Data were pooled from four double‐blind, placebo‐controlled trials.
Jena Shaw Tronieri   +5 more
wiley   +1 more source

GraphReco: Probabilistic Structure Recognition for Chemical Molecules

open access: yesChemistryOpen, EarlyView.
Molecule structure images are unfriendly for machine understanding, blocking productivity improvements in chemical data mining, drug discovery, and many other fields. We present a rule‐based probabilistic Optical Chemical Structure Recognition model to explain and tackle the ambiguity challenges in graph assembly.
Haidong Wang   +2 more
wiley   +1 more source

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