AIMC Topic: Machine Learning

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Use of Machine Learning Classifiers and Sensor Data to Detect Neurological Deficit in Stroke Patients.

Journal of medical Internet research
BACKGROUND: The pronator drift test (PDT), a neurological examination, is widely used in clinics to measure motor weakness of stroke patients.

Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning.

Scientific reports
Protein-protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large ...

A Human-Robot Co-Manipulation Approach Based on Human Sensorimotor Information.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This paper aims to improve the interaction and coordination between the human and the robot in cooperative execution of complex, powerful, and dynamic tasks. We propose a novel approach that integrates online information about the human motor functio...

MeSH Now: automatic MeSH indexing at PubMed scale via learning to rank.

Journal of biomedical semantics
BACKGROUND: MeSH indexing is the task of assigning relevant MeSH terms based on a manual reading of scholarly publications by human indexers. The task is highly important for improving literature retrieval and many other scientific investigations in ...

Global exponential stability of inertial memristor-based neural networks with time-varying delays and impulses.

Neural networks : the official journal of the International Neural Network Society
In this study, we investigate the global exponential stability of inertial memristor-based neural networks with impulses and time-varying delays. We construct inertial memristor-based neural networks based on the characteristics of the inertial neura...

Automatic feature learning using multichannel ROI based on deep structured algorithms for computerized lung cancer diagnosis.

Computers in biology and medicine
This study aimed to analyze the ability of extracting automatically generated features using deep structured algorithms in lung nodule CT image diagnosis, and compare its performance with traditional computer aided diagnosis (CADx) systems using hand...

A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages.

NeuroImage
Neuroimaging has made it possible to measure pathological brain changes associated with Alzheimer's disease (AD) in vivo. Over the past decade, these measures have been increasingly integrated into imaging signatures of AD by means of classification ...

Automatic migraine classification via feature selection committee and machine learning techniques over imaging and questionnaire data.

BMC medical informatics and decision making
BACKGROUND: Feature selection methods are commonly used to identify subsets of relevant features to facilitate the construction of models for classification, yet little is known about how feature selection methods perform in diffusion tensor images (...

Recursive least mean p-power Extreme Learning Machine.

Neural networks : the official journal of the International Neural Network Society
As real industrial processes have measurement samples with noises of different statistical characteristics and obtain the sample one by one usually, on-line sequential learning algorithms which can achieve better learning performance for systems with...