AIMC Topic: Machine Learning

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Identifying seizure onset zone from electrocorticographic recordings: A machine learning approach based on phase locking value.

Seizure
PURPOSE: Using a novel technique based on phase locking value (PLV), we investigated the potential for features extracted from electrocorticographic (ECoG) recordings to serve as biomarkers to identify the seizure onset zone (SOZ).

Gaussian process classification of superparamagnetic relaxometry data: Phantom study.

Artificial intelligence in medicine
MOTIVATION: Superparamagnetic relaxometry (SPMR) is an emerging technology that holds potential for use in early cancer detection. Measurement of the magnetic field after the excitation of cancer-bound superparamagnetic iron oxide nanoparticles (SPIO...

Few-shot learning in deep networks through global prototyping.

Neural networks : the official journal of the International Neural Network Society
Training a deep convolution neural network (CNN) to succeed in visual object classification usually requires a great number of examples. Here, starting from such a pre-learned CNN, we study the task of extending the network to classify additional cat...

Applying deep neural networks to unstructured text notes in electronic medical records for phenotyping youth depression.

Evidence-based mental health
BACKGROUND: We report a study of machine learning applied to the phenotyping of psychiatric diagnosis for research recruitment in youth depression, conducted with 861 labelled electronic medical records (EMRs) documents. A model was built that could ...

A machine learning approach for real-time modelling of tissue deformation in image-guided neurosurgery.

Artificial intelligence in medicine
OBJECTIVES: Accurate reconstruction and visualisation of soft tissue deformation in real time is crucial in image-guided surgery, particularly in augmented reality (AR) applications. Current deformation models are characterised by a trade-off between...

Clustering and Candidate Motif Detection in Exosomal miRNAs by Application of Machine Learning Algorithms.

Interdisciplinary sciences, computational life sciences
BACKGROUND: The clustering pattern and motifs give immense information about any biological data. An application of machine learning algorithms for clustering and candidate motif detection in miRNAs derived from exosomes is depicted in this paper. Re...

A novel deep learning algorithm for incomplete face recognition: Low-rank-recovery network.

Neural networks : the official journal of the International Neural Network Society
There have been a lot of methods to address the recognition of complete face images. However, in real applications, the images to be recognized are usually incomplete, and it is more difficult to realize such a recognition. In this paper, a novel con...

Improving deep convolutional neural networks with mixed maxout units.

PloS one
Motivated by insights from the maxout-units-based deep Convolutional Neural Network (CNN) that "non-maximal features are unable to deliver" and "feature mapping subspace pooling is insufficient," we present a novel mixed variant of the recently intro...