AIMC Topic: Algorithms

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BioWordVec, improving biomedical word embeddings with subword information and MeSH.

Scientific data
Distributed word representations have become an essential foundation for biomedical natural language processing (BioNLP), text mining and information retrieval. Word embeddings are traditionally computed at the word level from a large corpus of unlab...

Tractography and machine learning: Current state and open challenges.

Magnetic resonance imaging
Supervised machine learning (ML) algorithms have recently been proposed as an alternative to traditional tractography methods in order to address some of their weaknesses. They can be path-based and local-model-free, and easily incorporate anatomical...

Novel stochastic framework for automatic segmentation of human thigh MRI volumes and its applications in spinal cord injured individuals.

PloS one
Severe spinal cord injury (SCI) leads to skeletal muscle atrophy and adipose tissue infiltration in the skeletal muscle, which can result in compromised muscle mechanical output and lead to health-related complications. In this study, we developed a ...

Evolving neural networks to follow trajectories of arbitrary complexity.

Neural networks : the official journal of the International Neural Network Society
Many experiments have been performed that use evolutionary algorithms for learning the topology and connection weights of a neural network that controls a robot or virtual agent. These experiments are not only performed to better understand basic bio...

A RR interval based automated apnea detection approach using residual network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Apnea is one of the most common conditions that causes sleep-disorder breathing. With growing number of patients worldwide, more and more patients suffer from complications of apnea. But most of them stay untreated due to th...

A Channel-Projection Mixed-Scale Convolutional Neural Network for Motor Imagery EEG Decoding.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Motor imagery electroencephalography (EEG) decoding is an essential part of brain-computer interfaces (BCIs) which help motor-disabled patients to communicate with the outside world by external devices. Recently, deep learning algorithms using decomp...

Gene pathogenicity prediction of Mendelian diseases via the random forest algorithm.

Human genetics
The study of Mendelian diseases and the identification of their causative genes are of great significance in the field of genetics. The evaluation of the pathogenicity of genes and the total number of Mendelian disease genes are both important questi...

Statistical Approaches Based on Deep Learning Regression for Verification of Normality of Blood Pressure Estimates.

Sensors (Basel, Switzerland)
Oscillometric blood pressure (BP) monitors currently estimate a single point but do not identify variations in response to physiological characteristics. In this paper, to analyze BP's normality based on oscillometric measurements, we use statistical...

Development and Prospective Validation of a Machine Learning-Based Risk of Readmission Model in a Large Military Hospital.

Applied clinical informatics
BACKGROUND: Thirty-day hospital readmissions are a quality metric for health care systems. Predictive models aim to identify patients likely to readmit to more effectively target preventive strategies. Many risk of readmission models have been develo...

Flux prediction using artificial neural network (ANN) for the upper part of glycolysis.

PloS one
The selection of optimal enzyme concentration in multienzyme cascade reactions for the highest product yield in practice is very expensive and time-consuming process. The modelling of biological pathways is a difficult process because of the complexi...