AIMC Topic: Models, Theoretical

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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
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...

Imaging-based Machine-learning Models to Predict Clinical Outcomes and Identify Biomarkers in Pancreatic Cancer: A Scoping Review.

Annals of surgery
OBJECTIVE: To perform a scoping review of imaging-based machine-learning models to predict clinical outcomes and identify biomarkers in patients with PDAC.

Surrogate gradients for analog neuromorphic computing.

Proceedings of the National Academy of Sciences of the United States of America
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...

Molecular persistent spectral image (Mol-PSI) representation for machine learning models in drug design.

Briefings in bioinformatics
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...

HINGRL: predicting drug-disease associations with graph representation learning on heterogeneous information networks.

Briefings in bioinformatics
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 ...

Inverting the structure-property map of truss metamaterials by deep learning.

Proceedings of the National Academy of Sciences of the United States of America
Inspired by crystallography, the periodic assembly of trusses into architected materials has enjoyed popularity for more than a decade and produced countless cellular structures with beneficial mechanical properties. Despite the successful and steady...

Deep learning-based EEG analysis: investigating P3 ERP components.

Journal of integrative neuroscience
The neural processing of incoming stimuli can be analysed from the electroencephalogram (EEG) through event-related potentials (ERPs). The P3 component is largely investigated as it represents an important psychophysiological marker of psychiatric di...

Elucidation of dynamic microRNA regulations in cancer progression using integrative machine learning.

Briefings in bioinformatics
MOTIVATION: Empowered by advanced genomics discovery tools, recent biomedical research has produced a massive amount of genomic data on (post-)transcriptional regulations related to transcription factors, microRNAs, long non-coding RNAs, epigenetic m...

MG-BERT: leveraging unsupervised atomic representation learning for molecular property prediction.

Briefings in bioinformatics
MOTIVATION: Accurate and efficient prediction of molecular properties is one of the fundamental issues in drug design and discovery pipelines. Traditional feature engineering-based approaches require extensive expertise in the feature design and sele...

Simplified description of dynamics in neuromorphic resonant tunneling diodes.

Chaos (Woodbury, N.Y.)
In this article, the standard theoretical model accounting for a double barrier quantum well resonant tunneling diode (RTD) connected to a direct current source of voltage is simplified by representing its current-voltage characteristic with an analy...