Results 141 to 150 of about 95,260 (290)

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

ФГБУ «НИИ ГРИППА» Минздрава России

open access: yesMicrobiology Independent Research Journal, 2015
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doaj  

Machine Learning‐Assisted Infectious Disease Detection in Low‐Income Areas: Toward Rapid Triage of Dengue and Zika Virus Using Open‐Source Hardware

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study introduces an affordable machine learning platform for simultaneous dengue and zika detection using fluorine‐doped tin oxide thin films modified with gold nanoparticles and DNA aptamers. Designed for low‐cost, hardware‐limited devices (< $25), the model achieves 95.3% accuracy and uses only 9.4 kB of RAM, demonstrating viability for resource‐
Marina Ribeiro Batistuti Sawazaki   +3 more
wiley   +1 more source

Modernizing the Monroe Doctrine [PDF]

open access: green, 1917
William V. Pooley   +1 more
openalex   +1 more source

Robust Reinforcement Learning Control Framework for a Quadrotor Unmanned Aerial Vehicle Using Critic Neural Network

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Quadrotor unmanned aerial vehicle control is critical to maintain flight safety and efficiency, especially when facing external disturbances and model uncertainties. This article presents a robust reinforcement learning control scheme to deal with these challenges.
Yu Cai   +3 more
wiley   +1 more source

Enhanced Multitask Learning with Attention Sparse Routing Mechanism for Intelligent Diabetes Prediction

open access: yesAdvanced Intelligent Systems, EarlyView.
The model leverages patient time‐space information for pattern feature representations. Encoders extract first and second‐order features, aggregated with categorical embeddings and dense features. Task‐specific and shared experts use gated networks, with a dispatch layer routing information for diabetes risk evaluation and blood glucose prediction ...
Yingshuai Wang   +8 more
wiley   +1 more source

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