Results 201 to 210 of about 457,497 (309)

Harnessing Large Language Models to Advance Microbiome Research: From Sequence Analysis to Clinical Applications

open access: yesAdvanced Intelligent Discovery, EarlyView.
Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing   +4 more
wiley   +1 more source

Editorial: Psycho-physical stressors in youth sport performance. [PDF]

open access: yesFront Psychol
Bonavolontà V   +2 more
europepmc   +1 more source

A Machine Learning Model for Interpretable PECVD Deposition Rate Prediction

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study develops six machine learning models (k‐nearest neighbors, support vector regression, decision tree, random forest, CatBoost, and backpropagation neural network) to predict SiNx deposition rates in plasma‐enhanced chemical vapor deposition using hybrid production and simulation data.
Yuxuan Zhai   +8 more
wiley   +1 more source

Delivering project SCORE in competitive youth sport settings. [PDF]

open access: yesFront Sports Act Living
Ferreira M   +5 more
europepmc   +1 more source

Adaptive Autonomy in Microrobot Motion Control via Deep Reinforcement Learning and Path Planning Synergy

open access: yesAdvanced Intelligent Systems, EarlyView.
This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi   +3 more
wiley   +1 more source

KDLM: Lightweight Brain Tumor Segmentation via Knowledge Distillation

open access: yesAdvanced Intelligent Systems, EarlyView.
A lightweight student network is designed, which is based on multiscale and multilevel feature fusion and combined with the residual channel attention mechanism to achieve efficient feature extraction and fusion with very few parameters. A dual‐teacher collaborative knowledge distillation framework is proposed.
Baotian Li   +4 more
wiley   +1 more source

How does the Kids SIPsmartER program impact the sugar‐sweetened beverage intake of students: An investigation beyond total treatment effect in randomized controlled trial

open access: yesAmerican Journal of Agricultural Economics, EarlyView.
Abstract This study develops and empirically estimates a structural framework to decompose the causal pathways of multilevel behavioral interventions targeting adolescent health behaviors. We apply this framework to the Kids SIPsmartER (KSS) program, a 6‐month, school‐based intervention evaluated through a clustered randomized controlled trial in rural
Naveen Abedin   +5 more
wiley   +1 more source

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