medical-projects's repositories
automatic-ecg-diagnosis
Scripts and modules for training and testing neural network for ECG automatic classification. Companion code to the paper "Automatic diagnosis of the 12-lead ECG using a deep neural network".
biometricECG
An ECG based biometric model for specialised authentication systems
boundary-loss
Official code for "Boundary loss for highly unbalanced segmentation", runner-up for best paper award at MIDL 2019. Extended version in MedIA, volume 67, January 2021.
cs-8395-dl
Code for CS-8395: Deep Learning in Medical Image Computing
Deep-Learning-Classification-1
Methodology to classify shortage of medical tweets using deep learning algorithms; RNN, BiLSTM, and data visualizations.
Deep-Learning-with-Tensorflow2.x-projects
Deep learning (also known as deep structured learning) is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised. Deep-learning architectures such as deep neural networks, deep belief networks, recurrent neural networks and convolutional neural networks have been applied to fields including computer vision, machine vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, bioinformatics, drug design, medical image analysis, material inspection and board game programs, where they have produced results comparable to and in some cases surpassing human expert performance.
Domain-Expertise-Medical-Data-
Deep Learning and AI Domain Expertise: Medical Data - EHR [Electronic Health Records], Genomes Sequencing, Neuroscience, Biomedical.
DRKG
A knowledge graph and a set of tools for drug repurposing
DS-Net
Rank 1st in the public leaderboard of SemanticKITTI Panoptic Segmentation (2020-11-16)
E6040-super-resolution-project
Implementation in pytorch of a recent paper in deep adversarial learning for super resolution of medical images.
ecg
Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network
examples
Examples of training and inference with neural networks for biomedical electron microscopy image segmentation
H-DenseUNet
TMI 2018. H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes
MGMC
https://arxiv.org/abs/2005.06935
ml-lessons
Intro to deep learning for medical imaging lesson, by MD.ai
mri-tvtv
Overcoming Measurement Inconsistency in Deep Learning for Linear Inverse Problems: Applications in Medical Imaging
nibabel
Python package to access a cacophony of neuro-imaging file formats
niwidgets
Neuroimaging widgets for jupyter notebooks
Notes_And_Paper_Sharing
Thesis analysis, Interpretation, Reappearance, Study Notes, Engineering Notes, Deep learning, Neural computing, Medical image, Semantic analysis
PuzzleCAM
Puzzle-CAM: Improved localization via matching partial and full features.
resector
Algorithm to simulate resection surgery on brain MRI scans.
resseg-ijcars
An unsupervised learning strategy for postoperative brain cavity segmentation simulating resections during training
SlicerEPISURG
3D Slicer module to visualize the EPISURG dataset and segment postoperative brain resection cavities using deep learning.
SlicerTorchIO
3D Slicer module for TorchIO.
transferGWAS
Repository for transferGWAS, a deep learning method for performing genome-wide association studies on full medical imaging data.