AIMC Topic: Machine Learning

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Machine learning in cardiovascular magnetic resonance: basic concepts and applications.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Machine learning (ML) is making a dramatic impact on cardiovascular magnetic resonance (CMR) in many ways. This review seeks to highlight the major areas in CMR where ML, and deep learning in particular, can assist clinicians and engineers in improvi...

QTG-Finder: A Machine-Learning Based Algorithm To Prioritize Causal Genes of Quantitative Trait Loci in Arabidopsis and Rice.

G3 (Bethesda, Md.)
Linkage mapping is one of the most commonly used methods to identify genetic loci that determine a trait. However, the loci identified by linkage mapping may contain hundreds of candidate genes and require a time-consuming and labor-intensive fine ma...

Intelligent Analysis of Premature Ventricular Contraction Based on Features and Random Forest.

Journal of healthcare engineering
Premature ventricular contraction (PVC) is one of the most common arrhythmias in the clinic. Due to its variability and susceptibility, patients may be at risk at any time. The rapid and accurate classification of PVC is of great significance for the...

Cell fishing: A similarity based approach and machine learning strategy for multiple cell lines-compound sensitivity prediction.

PloS one
The prediction of cell-lines sensitivity to a given set of compounds is a very important factor in the optimization of in-vitro assays. To date, the most common prediction strategies are based upon machine learning or other quantitative structure-act...

Applications of Computer Modeling and Simulation in Cartilage Tissue Engineering.

Tissue engineering and regenerative medicine
BACKGROUND: Advances in cartilage tissue engineering have demonstrated noteworthy potential for developing cartilage for implantation onto sites impacted by joint degeneration and injury. To supplement resource-intensive in vivo and in vitro studies ...

Development of a Wearable Electrical Impedance Tomographic Sensor for Gesture Recognition With Machine Learning.

IEEE journal of biomedical and health informatics
A wearable electrical impedance tomographic (wEIT) sensor with 8 electrodes is developed to realize gesture recognition with machine learning algorithms. To optimize the wEIT sensor, gesture recognition rates are compared by using a series of electro...

Defining and distinguishing infant behavioral states using acoustic cry analysis: is colic painful?

Pediatric research
BACKGROUND: To characterize acoustic features of an infant's cry and use machine learning to provide an objective measurement of behavioral state in a cry-translator. To apply the cry-translation algorithm to colic hypothesizing that these cries soun...

Adaptive fault-tolerant consensus for a class of leader-following systems using neural network learning strategy.

Neural networks : the official journal of the International Neural Network Society
In this paper, the leader-following consensus problem of a class of nonlinearly multi-dimensional multi-agent systems with actuator faults is addressed by developing a novel neural network learning strategy. In order to achieve the desirable consensu...

A network underlying human higher-order motor control: Insights from machine learning-based lesion-behaviour mapping in apraxia of pantomime.

Cortex; a journal devoted to the study of the nervous system and behavior
Neurological patients with apraxia of pantomime provide us with a unique opportunity to study the neural correlates of higher-order motor function. Previous studies using lesion-behaviour mapping methods led to inconsistent anatomical results, report...

Bag of Samplings for computer-assisted Parkinson's disease diagnosis based on Recurrent Neural Networks.

Computers in biology and medicine
Parkinson's Disease (PD) is a clinical syndrome that affects millions of people worldwide. Although considered as a non-lethal disease, PD shortens the life expectancy of the patients. Many studies have been dedicated to evaluating methods for early-...