AIMC Topic: Machine Learning

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An analysis of a digital variant of the Trail Making Test using machine learning techniques.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: The goal of this work is to develop a digital version of a standard cognitive assessment, the Trail Making Test (TMT), and assess its utility.

Community-Wide Evaluation of Computational Function Prediction.

Methods in molecular biology (Clifton, N.J.)
A biological experiment is the most reliable way of assigning function to a protein. However, in the era of high-throughput sequencing, scientists are unable to carry out experiments to determine the function of every single gene product. Therefore, ...

A Pathological Brain Detection System based on Extreme Learning Machine Optimized by Bat Algorithm.

CNS & neurological disorders drug targets
AIM: It is beneficial to classify brain images as healthy or pathological automatically, because 3D brain images can generate so much information which is time consuming and tedious for manual analysis. Among various 3D brain imaging techniques, magn...

Metric Learning for Multi-atlas based Segmentation of Hippocampus.

Neuroinformatics
Automatic and reliable segmentation of hippocampus from MR brain images is of great importance in studies of neurological diseases, such as epilepsy and Alzheimer's disease. In this paper, we proposed a novel metric learning method to fuse segmentati...

Role of Artificial Intelligence Techniques (Automatic Classifiers) in Molecular Imaging Modalities in Neurodegenerative Diseases.

Current Alzheimer research
Artificial Intelligence (AI) is a very active Computer Science research field aiming to develop systems that mimic human intelligence and is helpful in many human activities, including Medicine. In this review we presented some examples of the exploi...

Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.

JAMA
IMPORTANCE: Deep learning is a family of computational methods that allow an algorithm to program itself by learning from a large set of examples that demonstrate the desired behavior, removing the need to specify rules explicitly. Application of the...

[A Classification Algorithm for Epileptic Electroencephalogram Based on Wavelet Multiscale Analysis and Extreme Learning Machine].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
The automatic classification of epileptic electroencephalogram(EEG)is significant in the diagnosis and therapy of epilepsy.A classification algorithm for epileptic EEG based on wavelet multiscale analysis and extreme learning machine(ELM)is proposed ...

Computational miRNomics.

Journal of integrative bioinformatics
Editorial The term MicroRNA or its contraction miRNA currently appears in 21,215 titles of abstracts, published between 1997 and now, available on Pubmed (2016-21-22:12:59 EET). 4,108 of these were published in 2016 alone which signifies the importan...