AIMC Topic: Humans

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Modulation of the dynamics of cerebellar Purkinje cells through the interaction of excitatory and inhibitory feedforward pathways.

PLoS computational biology
The dynamics of cerebellar neuronal networks is controlled by the underlying building blocks of neurons and synapses between them. For which, the computation of Purkinje cells (PCs), the only output cells of the cerebellar cortex, is implemented thro...

Mathematical foundations of moral preferences.

Journal of the Royal Society, Interface
One-shot anonymous unselfishness in economic games is commonly explained by social preferences, which assume that people care about the monetary pay-offs of others. However, during the last 10 years, research has shown that different types of unselfi...

Deep learning applications for the classification of psychiatric disorders using neuroimaging data: Systematic review and meta-analysis.

NeuroImage. Clinical
Deep learning (DL) methods have been increasingly applied to neuroimaging data to identify patients with psychiatric and neurological disorders. This review provides an overview of the different DL applications within psychiatry and compares DL model...

Intelligent Neutrosophic Diagnostic System for Cardiotocography Data.

Computational intelligence and neuroscience
Cardiotocography data uncertainty is a critical task for the classification in biomedical field. Constructing good and efficient classifier via machine learning algorithms is necessary to help doctors in diagnosing the state of fetus heart rate. The ...

Predictors of complications occurring after open and robot-assisted prostate cancer surgery: a retrospective evaluation of 1062 consecutive patients treated in a tertiary referral high volume center.

Journal of robotic surgery
To investigate factors associated with the risk of major complications after radical prostatectomy (RP) by the open (ORP) or robot-assisted (RARP) approach for prostate cancer (PCa) in a tertiary referral center. 1062 consecutive patients submitted t...

Deep learning-based auto-delineation of gross tumour volumes and involved nodes in PET/CT images of head and neck cancer patients.

European journal of nuclear medicine and molecular imaging
PURPOSE: Identification and delineation of the gross tumour and malignant nodal volume (GTV) in medical images are vital in radiotherapy. We assessed the applicability of convolutional neural networks (CNNs) for fully automatic delineation of the GTV...