AIMC Topic:
Models, Theoretical

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Enhanced compound-protein binding affinity prediction by representing protein multimodal information via a coevolutionary strategy.

Briefings in bioinformatics Mar 19, 2023
Due to the lack of a method to efficiently represent the multimodal information of a protein, including its structure and sequence information, predicting compound-protein binding affinity (CPA) still suffers from low accuracy when applying machine-l...
Protein Binding Models, Theoretical Proteins Machine Learning
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ASAS-NANP symposium: mathematical modeling in animal nutrition-Making sense of big data and machine learning: how open-source code can advance training of animal scientists.

Journal of animal science Jan 3, 2023
Advancements in precision livestock technology have resulted in an unprecedented amount of data being collected on individual animals. Throughout the data analysis chain, many bottlenecks occur, including processing raw sensor data, integrating multi...
Humans Artificial Intelligence Models, Theoretical Animals Big Data Machine Learning Software
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ASAS-NANP symposium: mathematical modeling in animal nutrition: agent-based modeling for livestock systems: the mechanics of development and application.

Journal of animal science Jan 3, 2023
Over the last three decades, agent-based modeling/model (ABM) has been one of the most powerful and valuable simulation-based decision modeling techniques used to study the complex dynamic interactions between animals and their environment. ABM is a ...
Systems Analysis Models, Theoretical Models, Biological Artificial Intelligence Animals Livestock
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Research progress on coupling artificial intelligence and eco-environmental models.

Ying yong sheng tai xue bao = The journal of applied ecology Jan 1, 2023
Artificial intelligence (AI) has been widely used in the eco-environment field, but with shortcomings in revealing the laws of natural science, such as insufficient generalization ability and poor interpretability. In order to overcome these shortage...
Artificial Intelligence Models, Theoretical
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ASAS-NANP symposium: mathematical modeling in animal nutrition: limitations and potential next steps for modeling and modelers in the animal sciences.

Journal of animal science Jun 1, 2022
The field of animal science, and especially animal nutrition, relies heavily on modeling to accomplish its day-to-day objectives. New data streams ("big data") and the exponential increase in computing power have allowed the appearance of "new" model...
Animals Ecosystem Agriculture Models, Theoretical Artificial Intelligence
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ASAS-NANP symposium: mathematical modeling in animal nutrition: the progression of data analytics and artificial intelligence in support of sustainable development in animal science.

Journal of animal science Jun 1, 2022
A renewed interest in data analytics and decision support systems in developing automated computer systems is facilitating the emergence of hybrid intelligent systems by combining artificial intelligence (AI) algorithms with classical modeling paradi...
Animals Data Science Artificial Intelligence Reproducibility of Results Models, Theoretical Sustainable Development
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Imaging-based Machine-learning Models to Predict Clinical Outcomes and Identify Biomarkers in Pancreatic Cancer: A Scoping Review.

Annals of surgery Mar 1, 2022
OBJECTIVE: To perform a scoping review of imaging-based machine-learning models to predict clinical outcomes and identify biomarkers in patients with PDAC.
Pancreatic Neoplasms Treatment Outcome Adenocarcinoma Humans Machine Learning Biomarkers, Tumor Models, Theoretical Prognosis
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Surrogate gradients for analog neuromorphic computing.

Proceedings of the National Academy of Sciences of the United States of America Jan 25, 2022
To rapidly process temporal information at a low metabolic cost, biological neurons integrate inputs as an analog sum, but communicate with spikes, binary events in time. Analog neuromorphic hardware uses the same principles to emulate spiking neural...
Neurons Models, Theoretical Models, Neurological Action Potentials Models, Biological Computers Brain Neural Networks, Computer Algorithms
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Molecular persistent spectral image (Mol-PSI) representation for machine learning models in drug design.

Briefings in bioinformatics Jan 17, 2022
Artificial intelligence (AI)-based drug design has great promise to fundamentally change the landscape of the pharmaceutical industry. Even though there are great progress from handcrafted feature-based machine learning models, 3D convolutional neura...
Molecular Structure Ligands Artificial Intelligence Machine Learning Neural Networks, Computer Models, Theoretical Models, Molecular Drug Design Protein Binding
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HINGRL: predicting drug-disease associations with graph representation learning on heterogeneous information networks.

Briefings in bioinformatics Jan 17, 2022
Identifying new indications for drugs plays an essential role at many phases of drug research and development. Computational methods are regarded as an effective way to associate drugs with new indications. However, most of them complete their tasks ...
Machine Learning Algorithms Computational Biology Models, Theoretical Humans Neural Networks, Computer Disease Information Services Drug Repositioning Pharmaceutical Preparations
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