Habib Mrad's Projects
Tool for inferring global ancestry proportions in admixed samples using deep learning
Anomaly detection system for heart diseases from ECG using machine learning
added all materials
Examples of using deep learning in Bioinformatics
Final project for CS224d
Efficient Multi-Scale 3D Convolutional Neural Network for Segmentation of 3D Medical Scans
This repository contains implementations and illustrative code to accompany DeepMind publications
DeepMod: a deep-learning tool for genomic-scale, strand-sensitive and single-nucleotide based detection of DNA modifications
Improving Base Calling Accuracy with MinION Flow Cell
Classification of Lung cancer slide images using deep-learning
Deep Learning tutorials in jupyter notebooks.
A Python library to de-identify medical records with state-of-the-art NLP methods.
This project related to a task on my Deep learning Nanodegree on Udacity
Chest Xray Classifier using CNNs and Transfer Learning. The jupyter notebook of interest is titled 'Xrays_alt.ipynb'
Predict Diabetes using Machine Learning.
Simple android application that help patients to manage their medical reports.
The objective of this project is to develop computational algorithm that can accurately detect cardiovascular related diseases. The dataset used in this project was obtained from the publically available UCI repository heart disease dataset. This dataset has been considered the benchmark dataset in the computational cardiovascular space. The features used in the development of this model are considered medically relevant attributes(as indicated in the literature) as they significantly contribute to the progression of cardiovascular disease.
A collection of python scripts to work with DICOM (Digital Imaging and Communications in Medicine) files.
Azure friendly DICOMweb part 18 .NET server with qido-rs, wado-rs, stow-rs, wado-uri RESTful implementation
Digital Pathology AI
Sparrow AI - API for disease diagnostics
CMSC389I Fall 2018 @ UMD
Dive into Machine Learning with Python Jupyter notebook and scikit-learn!
Deep Learning for Time Series Classification
Deep Learning for analysis of Congenital Heart Defect genomic variation
A Review of Deep Learning Methods on ECG Data