Results 81 to 90 of about 190,317 (312)

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

Advanced Experiment Design Strategies for Drug Development

Advanced Intelligent Discovery, EarlyView.
Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang, Anthony Harker, Mohan Edirisinghe, Maryam Parhizkar   +3 more
wiley   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

The Chronic Kidney Disease Model: A General Purpose Model of Disease Progression and Treatment

BMC Medical Informatics and Decision Making, 2011
Background Chronic kidney disease (CKD) is the focus of recent national policy efforts; however, decision makers must account for multiple therapeutic options, comorbidities and complications.
Patel Uptal D, Belasco Eric J, Orlando Lori A, Matchar David B   +3 more
doaj   +1 more source

MCMC Estimation of Markov Models for Ion Channels [PDF]

, 2011
Ivo Siekmann, Larry E. Wagner, David I. Yule, Colin Fox, David Bryant, Edmund J. Crampin, James Sneyd   +6 more
openalex   +1 more source

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

Advanced 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, Yefeng Yang, Tao Huang, Boyang Li   +3 more
wiley   +1 more source

Feature Fusion Based Audio-Visual Speaker Identification Using Hidden Markov Model under Different Lighting Variations [PDF]

, 2014
Md. Rabiul Islam, M. Abdus Sobhan
openalex   +1 more source

Large Language Model‐Based Chatbots in Higher Education

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci, Merve Eryilmaz, Ail K. Yetisen, Savas Tasoglu, Aydogan Ozcan   +4 more
wiley   +1 more source

Modelling the Cost-Effectiveness of Indacaterol/Glycopyrronium versus Salmeterol/Fluticasone Using a Novel Markov Exacerbation-Based Approach

International Journal of COPD, 2020
Bhavesh Lakhotia,1 Ronan Mahon,1 Florian S Gutzwiller,2 Andriy Danyliv,1 Ivan Nikolaev,2 Praveen Thokala3 1Novartis Ireland Limited, Dublin, Ireland; 2Novartis Pharma, Basel, AG, Switzerland; 3PT Health Economics Ltd, Sheffield, UKCorrespondence: Ronan ...
Lakhotia B, Mahon R, Gutzwiller FS, Danyliv A, Nikolaev I, Thokala P   +5 more
doaj  

Multiobjective Environmental Cleanup with Autonomous Surface Vehicle Fleets Using Multitask Multiagent Deep Reinforcement Learning

Advanced Intelligent Systems, EarlyView.
This study presents a multitask strategy for plastic cleanup with autonomous surface vehicles, combining exploration and cleaning phases. A two‐headed Deep Q‐Network shared by all agents is traineded via multiobjective reinforcement learning, producing a Pareto front of trade‐offs.
Dame Seck, Samuel Yanes, Manuel Perales, Daniel Gutiérrez, Sergio Toral   +4 more
wiley   +1 more source