AIMC Topic: Humans

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Image segmentation based on gray level and local relative entropy two dimensional histogram.

PloS one
Though traditional thresholding methods are simple and efficient, they may result in poor segmentation results because only image's brightness information is taken into account in the procedure of threshold selection. Considering the contextual infor...

Pragmatics, Theory of Mind and executive functions in schizophrenia: Disentangling the puzzle using machine learning.

PloS one
OBJECTIVE: Schizophrenia is associated with a severe impairment in the communicative-pragmatic domain. Recent research has tried to disentangle the relationship between communicative impairment and other domains usually impaired in schizophrenia, i.e...

Novel Deep Learning Network Analysis of Electrical Stimulation Mapping-Driven Diffusion MRI Tractography to Improve Preoperative Evaluation of Pediatric Epilepsy.

IEEE transactions on bio-medical engineering
OBJECTIVE: To investigate the clinical utility of deep convolutional neural network (DCNN) tract classification as a new imaging tool in the preoperative evaluation of children with focal epilepsy (FE).

The hunt for sORFs: A multidisciplinary strategy.

Experimental cell research
Growing evidence illustrates the shortcomings on the current understanding of the full complexity of the proteome. Previously overlooked small open reading frames (sORFs) and their encoded microproteins have filled important gaps, exerting their func...

Machine-learning-based computed tomography radiomic analysis for histologic subtype classification of thymic epithelial tumours.

European journal of radiology
PURPOSE: To evaluate the performance of machine-learning-based computed tomography (CT) radiomic analysis to differentiate high-risk thymic epithelial tumours (TETs) from low-risk TETs according to the WHO classification.

DeepSurvNet: deep survival convolutional network for brain cancer survival rate classification based on histopathological images.

Medical & biological engineering & computing
Histopathological whole slide images of haematoxylin and eosin (H&E)-stained biopsies contain valuable information with relation to cancer disease and its clinical outcomes. Still, there are no highly accurate automated methods to correlate histolopa...

A-phase classification using convolutional neural networks.

Medical & biological engineering & computing
A series of short events, called A-phases, can be observed in the human electroencephalogram (EEG) during Non-Rapid Eye Movement (NREM) sleep. These events can be classified in three groups (A1, A2, and A3) according to their spectral contents, and a...

Fusing Self-Organized Neural Network and Keypoint Clustering for Localized Real-Time Background Subtraction.

International journal of neural systems
Moving object detection in video streams plays a key role in many computer vision applications. In particular, separation between background and foreground items represents a main prerequisite to carry out more complex tasks, such as object classific...

[The adversarial dialogue].

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