Results 221 to 230 of about 6,917,983 (390)

A CNN‐LSTM Method Based on Voltage Deviation for Predicting the State of Health of Lithium‐Ion Batteries

Battery Energy, EarlyView.
We propose a convolutional neural network‐long short‐term memory (CNN‐LSTM) hybrid framework which aims to at estimate SOH of the battery. The results indicate that our model not only simplifies the computational complexity but also significantly enhances the precision of SOH predictions. ABSTRACT Ensuring the accurate estimation of the state of health
Fen Xiao, Wei Yang, Yanhuai Ding, Xiang Li, Kehang Zhang, Jiaxiong Liu   +5 more
wiley   +1 more source

Mapping Interictal activity in epilepsy using a hidden Markov model: A magnetoencephalography study

Human Brain Mapping, Volume 44, Issue 1, Page 66-81, January 2023., 2023
In this study, we use hidden Markov modeling (HMM) to create a unique statistical model of interictal brain activity for 10 pediatric epilepsy patients. This data‐driven model produces an output unique to each patient, and is used to localize the epileptogenic area(s).
Zelekha A. Seedat, Lukas Rier, Lauren E. Gascoyne, Harry Cook, Mark W. Woolrich, Andrew J. Quinn, Timothy P. L. Roberts, Paul L. Furlong, Caren Armstrong, Kelly St. Pier, Karen J. Mullinger, Eric D. Marsh, Matthew J. Brookes, William Gaetz   +13 more
wiley   +1 more source

A Bayesian network model for protein fold and remote homologue recognition [PDF]

, 2002
Alpan Raval, Zoubin Ghahramani, DL Wild
openalex   +1 more source

Transfer Learning‐Based Data‐Fusion Model Framework for State of Health Estimation of Power Battery Packs

Battery Energy, EarlyView.
To handle nonlinearity and feature coupling, a data‐driven aging model is proposed, employing dual Gaussian Process Regressions and transfer learning to enhance model efficiency and accuracy. Adaptive filtering refines the model by integrating aging features and output capacity, resulting in a closed‐loop data fusion framework for SOH estimation ...
Zhiqiang Lyu, Xinyuan Wei, Longxing Wu, Chunhui Liu   +3 more
wiley   +1 more source

Lasmiditan and Different Triptans in Menstrual Migraine: A Bayesian Network Meta-analysis. [PDF]

Pain Ther
Song Z, Guo Y, Gu J, Yang C, Qu R, Li J, Chen Z, Wang Z.   +7 more
europepmc   +1 more source

Bayesian Networks for Incorporation of Contextual Information in Target Recognition Systems [PDF]

, 2002
Keith D. Copsey, Andrew Webb
openalex   +1 more source

Comparing in silico flowsheet optimization strategies in biopharmaceutical downstream processes

Biotechnology Progress, EarlyView.
Abstract The challenging task of designing biopharmaceutical downstream processes is initially to select the type of unit operations, followed by optimizing their operating conditions. For complex flowsheet optimizations, the strategy becomes crucial in terms of duration and outcome.
Daphne Keulen, Myrto Apostolidi, Geoffroy Geldhof, Olivier Le Bussy, Martin Pabst, Marcel Ottens   +5 more
wiley   +1 more source

RETRACTED: Artificial intelligence for emergency medical care

Health Care Science, EarlyView., 2023
‘Applications of artificial intelligence in emergency medical service’. Abstract There is increasing research into the potential benefits of incorporating artificial intelligence (AI) and machine learning algorithms into emergency medical services. AI is finding new applications across a wide range of sectors, one of which is healthcare, where it is ...
Shivam Rajput, Pramod Kumar Sharma, Rishabha Malviya   +2 more
wiley   +1 more source

Expert Judgment Supporting a Bayesian Network to Model the Survival of Pancreatic Cancer Patients. [PDF]

Cancers (Basel)
Secchettin E, Paiella S, Azzolina D, Casciani F, Salvia R, Malleo G, Gregori D.   +6 more
europepmc   +1 more source

Analysis of molecular expression patterns and integration with other knowledge bases using probabilistic Bayesian network models

, 2000
Edward J. Moler, Shahzad I. Mian
openalex   +2 more sources