Results 201 to 210 of about 3,284,626 (292)

Simulated evaluation of large language model stepwise diagnostic reasoning with real-world chest pain encounters and Bayesian networks. [PDF]

BMC Med Inform Decis Mak
Safranek CW, Socrates V, Wright D, Huang T, Alashi A, McCann K, Taylor RA, Chartash D.   +7 more
europepmc   +1 more source

Machine learning–driven design of catalytic processes for sulfur dioxide oxidation: Lessons from the trenches

AIChE Journal, EarlyView.
Abstract Despite the growing use of ML in chemical engineering, the catalytic conversion of sulfur dioxide (SO2) to sulfur trioxide (SO3) remains underexplored from a data‐driven modeling perspective. This study evaluates an integrated workflow for literature‐derived SO2 oxidation data, combining data curation, preprocessing assessment, machine ...
Farough Agin, Jules Thibault, Clémence Fauteux‐Lefebvre   +2 more
wiley   +1 more source

Data-driven Bayesian networks for risk scenario mapping of Falls from height accidents. [PDF]

PLoS One
Li J, Wang T.
europepmc   +1 more source

Bayesian networks [PDF]

, 2011
openaire   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Correction: A guide to bayesian networks software for structure and parameter learning, with a focus on causal discovery tools. [PDF]

Front Syst Biol
Canonaco F, Gaudillo J, Astrologo N, Stella F, Acerbi E.   +4 more
europepmc   +1 more source

Embedded Morgan Fingerprints for More Efficient Molecular Property Predictions With Machine Learning

Advanced Intelligent Discovery, EarlyView.
High dimensionality of Morgan fingerprints causes overfitting and slow training. Embedded Morgan Fingerprint (eMFP) compresses this encoding while keeping key structural information intact. Tested on five regression models across three databases for HOMO–LUMO gap prediction, eMFP outperforms standard fingerprints, training faster on large, high ...
Emilio Nuñez‐Andrade, Isaac Vidal‐Daza, Rafael Gómez‐Bombarelli, James W. Ryan, Francisco J. Martin‐Martinez   +4 more
wiley   +1 more source

A hybrid approach combining Bayesian networks and logistic regression for enhancing risk assessment. [PDF]

Sci Rep
Wei X, Dong Y.
europepmc   +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

A guide to bayesian networks software for structure and parameter learning, with a focus on causal discovery tools. [PDF]

Front Syst Biol
Canonaco F, Gaudillo J, Astrologo N, Stella F, Acerbi E.   +4 more
europepmc   +1 more source