Results 171 to 180 of about 53,385 (259)

Constructing Artificial Features with Grammatical Evolution for the Motor Symptoms of Parkinson's Disease. [PDF]

Bioengineering (Basel)
Psathas A, Tsoulos IG, Giannakeas N, Tzallas A, Charilogis V.   +4 more
europepmc   +1 more source

Closing the Gate Before the Horse is out of the Barn: A Model to Effectively Predict the First Fall in Patients with Parkinson's Disease

Movement Disorders Clinical Practice, EarlyView.
Abstract Background Most fall‐prediction models in Parkinson's disease (PD) rely on prior falls, limiting prevention. The Waiting Room of the Future (WROTF) platform collects standardized motor and cognitive measures during routine visits, integrated into electronic health records (EHR).
Saar Anis, Eric Zimmerman, Maxime Munyeshyaka, Hubert H. Fernandez, Anson B. Rosenfeldt, Jay L. Alberts   +5 more
wiley   +1 more source

SIGNAL: Dataset for Semantic and Inferred Grammar Neurological Analysis of Language. [PDF]

Sci Data
Komissarenko A, Voloshina E, Cheveleva A, Semenkov I, Serikov O, Ossadtchi A.   +5 more
europepmc   +1 more source

Development and Validation of a Consensus Machine Learning–Derived Signature to Predict Survival and Treatment Benefits in Breast Cancer

Medicine Advances, EarlyView.
The consensus machine learning–derived prognostic signature (CMDPS) was developed by integrating 10 independent breast cancer cohorts and 76 algorithm combinations, which identified 19 robust survival‐associated genes. The CMDPS demonstrated superior prognostic performance compared to clinical features and 62 published transcriptome signatures ...
Guangyang Cheng, Zhan Wang, Fu Peng, Shuai Yang, Yudi Xu, Hongzhuo Qin, Run Shi, Zhaokai Zhou   +7 more
wiley   +1 more source

High cognitive violation of expectations is compromised in cerebellar ataxia. [PDF]

Elife
Daniel L, Vakil E, Saban W.
europepmc   +1 more source

Recent Advances in the Laser‐Based Fabrication and Applications of High‐Entropy Alloy Nanoparticles

MetalMat, EarlyView.
This review presents recent advances in the laser‐based fabrication of high‐entropy alloy nanoparticles, focusing on scalable, environmentally friendly, and compositionally tunable synthesis methods. It highlights the critical influence of laser parameters on nanoparticle size, phase, and morphology, enabling tailored properties for applications in ...
Bibek Kumar Singh, Rajesh Rawat, Archana Tiwari, Venugopal Rao Soma, Ajay Tripathi   +4 more
wiley   +1 more source

Correction to "Intratumoral vidutolimod as monotherapy or in combination with pembrolizumab in patients with programmed cell death 1 blockade-resistant melanoma: Final analysis from a phase 1b study". [PDF]

Cancer
europepmc   +1 more source

New Opportunities For the Integration of Artificial Intelligence With Materials Science: From Large Language Models to Embodied Large Models

Materials Genome Engineering Advances, EarlyView.
This review first introduces the diversified applications of large language models in materials discovery. Subsequently, the evolution of autonomous experimentation platforms empowered by large language models is analyzed. Finally, four key future research interests are proposed to develop embodied large models for driving autonomous experimentation ...
Zhen Song, Yishuai Cai, Yadong Yu, Pan Xiang, Minglong Li, Zhe Liu, Mengyan Dai   +6 more
wiley   +1 more source

Quantitative Diffusion and T2 Mapping Using RF‐Modulated Phase‐Based Gradient Echo Imaging

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose To introduce and evaluate the feasibility of a novel RF‐phase modulated gradient echo (GRE) method for quantitative diffusion MRI, aimed at mitigating geometric distortion and enabling high‐resolution 3D quantitative diffusion/T2 mapping as a complementary alternative to conventional DWI.
Daiki Tamada, Ali Pirasteh, David F. Jarrard, Diego Hernando, Scott B. Reeder   +4 more
wiley   +1 more source

Community size rather than grammatical complexity better predicts Large Language Model accuracy in a novel Wug Test. [PDF]

PLoS One
Pantelidou N, Leivada E, Montero R, Morosi P.   +3 more
europepmc   +1 more source