Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
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Updated
Oct 19, 2024 - HTML
Medical imaging is the technique and process of creating visual representations of the interior of a body for clinical analysis, and medical intervention.
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
webpage for maintaining the list of openly available DL, ML, RL, Vision, NLP, Optimization courses
Large-Scale Multi-Class Image-Based Cell Classification with Deep Learning
The NTUA Parkinson's Dataset
⚕️📊 A simple overlay tool that adds debugging information over the canvas #CornerstoneJS
Experimental Platform for Human AI Collaboration - Code for the paper "Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imaging" published at FAccT 2022
Health AI
Egyptian Coffins website - Jekyll, material, bootstrap, jquery
A web application which detects brain tumours and projects the model of the brain in AR.
Pediatric pneumonia image classification with (strongly) imbalanced data via Pytorch 🫁
My Second WebPage Templet depending on HTML + CSS only. Personal webpage containing all information that your Patients need "Education & Experiance & Skills & Portfolio & Blog & Contacts" available for Doctors, Dentists, Pharmacists and Surgeons. With the vision of Eng/ Osama Elzero
A patch-based Gastroscopic Classifier web app with Python backend using Flask micro-framework and PyTorch modified Resnet-34 Convolutional Neural Network.
A Progressive Web App DICOM Viewer/Converter
A repository for an automated system using object detection and machine learning techniques to diagnose wrist abnormalities in children, adolescents, and young adults, providing high accuracy and precision in diagnosis through a user-friendly mobile application.
An AI integrated website, where the user will get to know whether he or she is infected by viruses or diseases based on their medical documentations.
Multiple Disease Diagnosis System using Medical Images
This project is one of the projects required for AI for Business Nanodegree
[AIIM] Recall & Precision results of the UTA7 statistical analysis.
Counting cells in a blood smear using convolution as the pattern matching strategy