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Single-image super-resolution microscopy
A deep learning pre-trained model based on the Enhanced Super Resolution Generative Adversarial Network (ESRGAN) is used to obtain a Super-Resolution (SR) image from a...-
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Private jointfusion_hackathon
A joint fusion DL model was developed to predict ASD from structural and functional connectome brain features extracted form the ABIDE MRI and fMRI datasets. The DL algorithm... -
Private bone age assessment
The goal this DL model is to predict the age of a subject by looking at his/her X-ray image of the hand. This DL algorithm was developed to address a challenge posed on thee... -
AGC: Autism Graph Classifier
AGC is designed to support the processing and analysis of brain connectivity data by leveraging standard outputs from widely used neuroimaging pipelines such as CPAC and...-
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Private neuroAnDetect
Semi-supervised approach to anomaly detection for neuro-imaging. The method generates segmentation of abnormal tissues that can be used to support medical reporting. The... -
DELTA: Dense Electromyography for Long-Term Adaptive control
The DELTA dataset, namely ”Dense Electromyography for Long-Term Adaptive control”, holds significance in the realm of prosthetic applications, featuring High Density surface... -
Integrating Direct Intracranial Stimulation with the Human Connectome
Cortical and subcortical direct electrical stimulation (DES) coordinates in MNI space, anonymized patients’ demographic data, and aggregated functional maps for the 12... -
Human and mouse gene regulatory networks
The dataset was built by considering gene expression data related to 6 different organs (liver, lung, brain, skin, bone marrow, heart), obtained by control samples available... -
Stroke and sepsi
The considered stroke dataset (DOI:10.17632/x8ygrw87jw.1, DOI:10.1016/j.artmed.2019.101723) was pre-processed by removing attributes with more than 30% missing values, by...
