Results 141 to 150 of about 28,119 (261)

DinoFlow: Self‐supervised pretraining in flow cytometry enables accurate detection of common hematopathological disorders

Cytometry Part B: Clinical Cytometry, EarlyView.
Abstract Flow cytometry is an essential component of routine hematological lab testing. Many computational methods have been proposed for the analysis of flow cytometry data, but most have focused on supervised learning for just one or a few specific disorders.
Brendan O'Fallon, Muir Morrison, Mattia Medina Grespan, Nicholas C. Spies, David P. Ng   +4 more
wiley   +1 more source

RMIS-Net: a fast medical image segmentation network based on multilayer perceptron. [PDF]

PeerJ Comput Sci
Zhang B, Xu G, Xing Y, Li N, Li D.
europepmc   +1 more source

Multi‐factor coupling effects in hydraulic fracturing of laminated shale: Experimental insights and physics‐informed neural network‐driven optimization

Deep Underground Science and Engineering, EarlyView.
This study establishes a multi‐factor coupling framework for predicting breakdown pressure in laminated shale by integrating experimental hydraulic fracturing tests, physics‐informed neural networks (PINNs), and Sobol sensitivity analysis. It reveals how differential stress, the bedding dip angle, and the injection rate interact to influence fracture ...
Tao Wang, Guoyao Xu, Liyuan Liu, Yao Zhang, Sitao Zhu, Hongyang Chu, Kaikai Zhao   +6 more
wiley   +1 more source

IPO: An Improved Parrot Optimizer for Global Optimization and Multilayer Perceptron Classification Problems. [PDF]

Biomimetics (Basel)
Li F, Dai C, Hussien AG, Zheng R.
europepmc   +1 more source

AI‐based localization of the epileptogenic zone using intracranial EEG

Epilepsia Open, EarlyView.
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida, Yipeng Zhang, Sotaro Kanai, Richard Staba, Vwani Roychowdhury, Hiroki Nariai   +5 more
wiley   +1 more source

Predicting football match outcomes: a multilayer perceptron neural network model based on technical statistics indicators of the FIFA world Cup. [PDF]

Front Sports Act Living
Luo Y, Quan T, Cao Y.
europepmc   +1 more source

Triboelectric nanogenerators for vehicle intelligent cockpits

FlexMat, EarlyView.
Converting mechanical stimuli from drivers and vehicle motion into electrical signals, triboelectric nanogenerators provide promising interfaces toward passive, flexible, distributed and intelligent sensing for next‐generation automotive cockpits to support three core functional dimensions: driver state monitoring, vehicle state monitoring, and human ...
Haiqiu Tan, Shiquan Lü, Xiangwei Meng, Huiying Zhang, Wenxing Zhang, Dongxian Sun, Xiao Lu, Lei Wang, Haodong Zhang, William W. Yu   +9 more
wiley   +1 more source

A novel framework for TER allocation using multilayer perceptron and intuitionistic fuzzy Z numbers for talent management. [PDF]

Sci Rep
Yang T.
europepmc   +1 more source

Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models

Journal of Forecasting, EarlyView.
ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly, Pooja Sengupta, Divya Aggarwal   +2 more
wiley   +1 more source

OPTIMIZING MULTILAYER PERCEPTRON NEURAL NETWORK HYPERPARAMETERS

Journal of Process Management and New Technologies
Ivana PETKOVSKI
doaj   +1 more source