Machine Learning based Diabetes Detection
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Updated
Jan 18, 2024 - Jupyter Notebook
Machine Learning based Diabetes Detection
Kurtlab's code for BraTS 2023 submission
This GitHub repository hosts the notebooks and tools developed as part of this thesis to automate the extraction, processing, and analysis of data from the MICCAI 2023 conference, aiding in the systematic review and providing a structured foundation for further research in this crucial area.
Create a medical imaging application based on different DL models.
This repository aims to present a general, customazible pipeline for MRI images based on a single configuration file (in .json format) that has different flags and according to them, a certain pre-processing procedure with desired steps is performed.
Chinese-Medical-Question-Answering-Data
Welcome to the official repository of HF-Fed: Hierarchical based customized Federated Learning Framework for X-Ray Imaging accepted in MICCAI Worshop 2024.
This is a simple neural network model trainer, (first named tensor dumbass), that is specially designed for medical AI and ease of use. Note that this code is specially created to work with larger tasks for classification tasks and some generative tasks. Furthermore this code is mainly aimed to help to cure cancer using Crisper technologies.
Comparison of Feature Extraction techniques for COVID19 diagnosis of CT scans.
A pharmacokinetic model for predicting propofol concentration in a patient's body
Final Project for CS 229 - Machine Learning (Fall 2022)
🧠 A deep learning model that classifies brain images as either having a tumor or not.
On the evaluation of deep learning interpretability methods for medical images under the scope of faithfulness
GPT2-774M model, fine-tuned on all public information and papers (up to 2021) related to Chronic Fatigue Syndrome/Myalgic Encephalomyelitis
Large language model of Medical AI, General Medical AI (GMAI)
Predict which cell is cancerous with 96% accuracy using SVM machine learning algorithm.
AI application on Django 2 - "MedRadService"
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