Results 201 to 210 of about 29,862 (274)

A wavelet-based frequency-domain approach for accurate multi-crop disease detection. [PDF]

open access: yesSci Rep
Zhao J   +7 more
europepmc   +1 more source

Putting the X on TH/EX [PDF]

open access: yes, 2001
Atkinson, M
core  

Challenges and Opportunities in Machine Learning for Light‐Emitting Polymers

open access: yesMacromolecular Rapid Communications, EarlyView.
The performance of light‐emitting polymers emerges from coupled effects of chemical diversity, morphology, and exciton dynamics across multiple length scales. This Perspective reviews recent design strategies and experimental challenges, and discusses how machine learning can unify descriptors, data, and modeling approaches to efficiently navigate ...
Tian Tian, Yinyin Bao
wiley   +1 more source

Integrating Chain‐of‐Thought and Retrieval Augmented Generation Enhances Rare Disease Diagnosis From Clinical Notes

open access: yesMedicine Bulletin, EarlyView.
ABSTRACT Background Several studies show that large language models (LLMs) struggle with phenotype‐driven gene prioritization for rare diseases. These studies typically use Human Phenotype Ontology (HPO) terms to prompt foundation models such as GPT and LLaMA to predict candidate genes.
Zhanliang Wang   +3 more
wiley   +1 more source

Alzheimer's Biomarkers and Visuospatial Cognition in Parkinson's Disease: Modification by α‐Synuclein and Mediation of Age Effects

open access: yesMovement Disorders Clinical Practice, EarlyView.
Abstract Background Visuospatial deficits in Parkinson's disease (PD) often precede dementia and complicate daily functioning. Alzheimer's disease (AD) pathology and α‐synuclein aggregation frequently co‐occur in PD, but their combined impact on cognition is unclear.
David Ledingham   +8 more
wiley   +1 more source

Quality Assessment of Solar EUV Remote Sensing Images Using Multi-Feature Fusion. [PDF]

open access: yesSensors (Basel)
Dai S   +8 more
europepmc   +1 more source

TopoMAS: Large Language Model Driven Topological Materials Multi‐Agent System

open access: yesMaterials Genome Engineering Advances, EarlyView.
TopoMAS is an interactive multi‐agent framework that revolutionizes topological materials discovery through human–AI collaborative intelligence. The system integrates natural language processing, knowledge retrieval from literature and databases, crystal structure generation, and automated first‐principles calculations within a unified workflow.
Baohua Zhang   +5 more
wiley   +1 more source

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