AIMC Topic:
Models, Theoretical

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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...
Neural Networks, Computer Artificial Intelligence Models, Molecular Molecular Structure Ligands Protein Binding Models, Theoretical Machine Learning Drug Design
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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 ...
Neural Networks, Computer Disease Pharmaceutical Preparations Humans Algorithms Models, Theoretical Machine Learning Information Services Drug Repositioning Computational Biology
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Inverting the structure-property map of truss metamaterials by deep learning.

Proceedings of the National Academy of Sciences of the United States of America Jan 4, 2022
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...
Construction Materials Deep Learning Models, Theoretical
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Deep learning-based EEG analysis: investigating P3 ERP components.

Journal of integrative neuroscience Dec 30, 2021
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...
Electroencephalography Event-Related Potentials, P300 Deep Learning Models, Theoretical Humans
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Elucidation of dynamic microRNA regulations in cancer progression using integrative machine learning.

Briefings in bioinformatics Nov 5, 2021
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...
MicroRNAs Gene Regulatory Networks Models, Theoretical Breast Neoplasms Disease Progression Machine Learning Humans Female
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MG-BERT: leveraging unsupervised atomic representation learning for molecular property prediction.

Briefings in bioinformatics Nov 5, 2021
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...
Neural Networks, Computer Models, Theoretical
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Simplified description of dynamics in neuromorphic resonant tunneling diodes.

Chaos (Woodbury, N.Y.) Nov 1, 2021
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...
Models, Theoretical Neurons Algorithms Neural Networks, Computer Prospective Studies
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High-generalization deep sparse pattern reconstruction: feature extraction of speckles using self-attention armed convolutional neural networks.

Optics express Oct 25, 2021
Light scattering is a pervasive problem in many areas. Recently, deep learning was implemented in speckle reconstruction. To better investigate the key feature extraction and generalization abilities of the networks for sparse pattern reconstruction,...
Neural Networks, Computer Tomography, X-Ray Computed Image Processing, Computer-Assisted Signal-To-Noise Ratio Models, Theoretical
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Automatic contour segmentation of cervical cancer using artificial intelligence.

Journal of radiation research Sep 13, 2021
In cervical cancer treatment, radiation therapy is selected based on the degree of tumor progression, and radiation oncologists are required to delineate tumor contours. To reduce the burden on radiation oncologists, an automatic segmentation of the ...
Teaching Imaging, Three-Dimensional Female Diffusion Magnetic Resonance Imaging Humans Models, Theoretical Image Processing, Computer-Assisted Uterine Cervical Neoplasms Artificial Intelligence Radiation Oncology
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Integrating multi-scale neighbouring topologies and cross-modal similarities for drug-protein interaction prediction.

Briefings in bioinformatics Sep 2, 2021
MOTIVATION: Identifying the proteins that interact with drugs can reduce the cost and time of drug development. Existing computerized methods focus on integrating drug-related and protein-related data from multiple sources to predict candidate drug-t...
Humans Machine Learning Proteins Protein Binding Algorithms Pharmaceutical Preparations Computational Biology Drug Development Reproducibility of Results Support Vector Machine Models, Theoretical
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