AIMC Topic: Algorithms

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k-Space-based coil combination via geometric deep learning for reconstruction of non-Cartesian MRSI data.

Magnetic resonance in medicine
PURPOSE: State-of-the-art whole-brain MRSI with spatial-spectral encoding and multichannel acquisition generates huge amounts of data, which must be efficiently processed to stay within reasonable reconstruction times. Although coil combination signi...

A hybrid learning-based hysteresis compensation strategy for surgical robots.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: The hysteretic forces arising from the electric cables that externally run along the robotic joints are the main disturbance to the precise parameter estimation of gravity compensation model, for the Master Tool Manipulator (MTM) of the d...

Automated AI labeling of optic nerve head enables insights into cross-ancestry glaucoma risk and genetic discovery in >280,000 images from UKB and CLSA.

American journal of human genetics
Cupping of the optic nerve head, a highly heritable trait, is a hallmark of glaucomatous optic neuropathy. Two key parameters are vertical cup-to-disc ratio (VCDR) and vertical disc diameter (VDD). However, manual assessment often suffers from poor a...

A supervised clustering MCMC methodology for large categorical feature spaces.

Statistical methods in medical research
There is a well-established tradition within the statistics literature that explores different techniques for reducing the dimensionality of large feature spaces. The problem is central to machine learning and it has been largely explored under the u...

Search for H-Bonded Motifs in Liquid Ethylene Glycol Using a Machine Learning Strategy.

The journal of physical chemistry. B
Trajectories of atomic positions derived from molecular dynamics (AIMD) simulations of H-bonded liquids contain a wealth of information on dominant structural motifs and recurrent patterns of association. Extracting this information from a detailed ...

In silico drug repositioning using deep learning and comprehensive similarity measures.

BMC bioinformatics
BACKGROUND: Drug repositioning, meanings finding new uses for existing drugs, which can accelerate the processing of new drugs research and development. Various computational methods have been presented to predict novel drug-disease associations for ...

Blood Biomarkers Predict Cardiac Workload Using Machine Learning.

BioMed research international
INTRODUCTION: Rate pressure product (the product of heart rate and systolic blood pressure) is a measure of cardiac workload. Resting rate pressure product (rRPP) varies from one individual to the next, but its biochemical/cellular phenotype remains ...

Pedestrian attribute recognition using two-branch trainable Gabor wavelets network.

PloS one
Keeping an eye on pedestrians as they navigate through a scene, surveillance cameras are everywhere. With this context, our paper addresses the problem of pedestrian attribute recognition (PAR). This problem entails recognizing attributes such as age...

Current directions in combining simulation-based macromolecular modeling approaches with deep learning.

Expert opinion on drug discovery
: Structure-guided drug discovery relies on accurate computational methods for modeling macromolecules. Simulations provide means of predicting macromolecular folds, of discovering function from structure, and of designing macromolecules to serve as ...