Integrating machine learning to uncover homogeneous catalytic mechanisms in N‐vinyl‐pyrrolidone synthesis
Sign Up to like & getrecommendations! Published in 2024 at "AIChE Journal"
DOI: 10.1002/aic.18724
Abstract: Combining machine learning, density functional theory (DFT) calculation, and kinetic modeling offers significant advantages in studying reactions under complex conditions, enabling a detailed exploration of reaction mechanisms. Artificial neural network (ANN) models accurately predict and… read more here.
Keywords: reaction; homogeneous catalytic; machine learning; integrating machine ... See more keywords
Integrating Machine Learning into Free Energy Perturbation Workflows
Sign Up to like & getrecommendations! Published in 2025 at "Journal of Chemical Information and Modeling"
DOI: 10.1021/acs.jcim.5c01449
Abstract: Free energy perturbation (FEP) methods are among the most accurate tools in structure-based drug design for predicting protein–ligand binding affinities. However, their adoption remains limited due to high computational demands and complex setup procedures. This… read more here.
Keywords: integrating machine; machine learning; free energy; energy perturbation ... See more keywords
Toward Precision Agriculture: Integrating Machine Learning Techniques for Smart Farming Systems
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3480868
Abstract: Smart agriculture holds a transformative potential, driven by cutting-edge technologies, in revolutionizing the global food production sector and enhancing food safety measures. This is achieved by leveraging the capabilities of smart maps, artificial intelligence, and… read more here.
Keywords: agriculture integrating; toward precision; precision; precision agriculture ... See more keywords
Clinical approaches for integrating machine learning for patients with lymphoma: Current strategies and future perspectives.
Sign Up to like & getrecommendations! Published in 2023 at "British journal of haematology"
DOI: 10.1111/bjh.18861
Abstract: Machine learning (ML) approaches have been applied in the diagnosis and prediction of haematological malignancies. The consideration of ML algorithms to complement or replace current standard of care approaches requires investigation into the methods used… read more here.
Keywords: integrating machine; machine; machine learning; learning patients ... See more keywords
Integrating machine learning to construct aberrant alternative splicing event related classifiers to predict prognosis and immunotherapy response in patients with hepatocellular carcinoma
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Pharmacology"
DOI: 10.3389/fphar.2022.1019988
Abstract: Introduction: In hepatocellular carcinoma (HCC), alternative splicing (AS) is related to tumor invasion and progression. Methods: We used HCC data from a public database to identify AS subtypes by unsupervised clustering. Through feature analysis of… read more here.
Keywords: integrating machine; hepatocellular carcinoma; hcc; alternative splicing ... See more keywords