AIMC Topic:
Computer Simulation

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HPO2Vec+: Leveraging heterogeneous knowledge resources to enrich node embeddings for the Human Phenotype Ontology.

Journal of biomedical informatics
BACKGROUND: In precision medicine, deep phenotyping is defined as the precise and comprehensive analysis of phenotypic abnormalities, aiming to acquire a better understanding of the natural history of a disease and its genotype-phenotype associations...

Using machine learning to characterize heart failure across the scales.

Biomechanics and modeling in mechanobiology
Heart failure is a progressive chronic condition in which the heart undergoes detrimental changes in structure and function across multiple scales in time and space. Multiscale models of cardiac growth can provide a patient-specific window into the p...

A diversity of interneurons and Hebbian plasticity facilitate rapid compressible learning in the hippocampus.

Nature neuroscience
The hippocampus is able to rapidly learn incoming information, even if that information is only observed once. Furthermore, this information can be replayed in a compressed format in either forward or reverse modes during sharp wave-ripples (SPW-Rs)....

Single-Particle Diffusion Characterization by Deep Learning.

Biophysical journal
Diffusion plays a crucial role in many biological processes including signaling, cellular organization, transport mechanisms, and more. Direct observation of molecular movement by single-particle-tracking experiments has contributed to a growing body...

Estimation of the radiation dose in pregnancy: an automated patient-specific model using convolutional neural networks.

European radiology
OBJECTIVES: The conceptus dose during diagnostic imaging procedures for pregnant patients raises health concerns owing to the high radiosensitivity of the developing embryo/fetus. The aim of this work is to develop a methodology for automated constru...

Short-term synaptic plasticity expands the operational range of long-term synaptic changes in neural networks.

Neural networks : the official journal of the International Neural Network Society
The brain is highly plastic, with synaptic weights changing across a wide range of time scales, from hundreds of milliseconds to days. Changes occurring at different temporal scales are believed to serve different purposes, with long-term changes for...

DeepConv-DTI: Prediction of drug-target interactions via deep learning with convolution on protein sequences.

PLoS computational biology
Identification of drug-target interactions (DTIs) plays a key role in drug discovery. The high cost and labor-intensive nature of in vitro and in vivo experiments have highlighted the importance of in silico-based DTI prediction approaches. In severa...

fastJT: An R package for robust and efficient feature selection for machine learning and genome-wide association studies.

BMC bioinformatics
BACKGROUND: Parametric feature selection methods for machine learning and association studies based on genetic data are not robust with respect to outliers or influential observations. While rank-based, distribution-free statistics offer a robust alt...

Enabling machine learning in X-ray-based procedures via realistic simulation of image formation.

International journal of computer assisted radiology and surgery
PURPOSE: Machine learning-based approaches now outperform competing methods in most disciplines relevant to diagnostic radiology. Image-guided procedures, however, have not yet benefited substantially from the advent of deep learning, in particular b...