BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix
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Updated
Mar 9, 2024 - Python
BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix
SHEPHERD: Deep learning for diagnosing patients with rare genetic diseases
Code for "Graph-Evolving Meta-Learning for Low-Resource Medical Dialogue Generation". [AAAI 2021]
A Deep Learning Based approach for diagnosis of Schizophrenia using EEG brain recordings
Using TensorFlow Object Detection API to detect blood cells
Clustering Analysis of all available research data on the Iowa Gambling Task(list of sources in readme) using R. The Scripts produce the output for the most common archetypes among the dataset of one researcher using PCA.
Early detection of Autism Spectrum Disorder (ASD) is crucial for children's development, yet the diagnostic procedure remains challenging. EyeTism employs machine learning on eye tracking data from both high-functioning ASD and typically developing children (TD) to create a diagnostic tool based on their distinct visual attention patterns.
Code for my Master Thesis project on "Prompting Techniques for Natural Language Generation in the Medical Domain" at the University of Bologna
In this repository, you'll find Prolog code covering a range of questions, all designed to aid your learning journey.
A RESTful API using Flask and XGBoost to predict diabetes in Pima Indians based on various diagnostic measurements. Includes training, saving the best model, and testing the API using Python requests.
Bayesian Network aiming to help in endometriosis diagnosis.
A Prolog expert system designed for simple disease diagnosis using backward-chaining and a certainty factor system.
Implemented Several ML Techniques for Parkinson’s Detection with Speech Signals- Machine Learning Course Project
This repository contains a MATLAB project for malaria detection in microscopic images. It includes a MATLAB app and a standalone script that apply a malaria cell prediction algorithm. The project aims to assist in automating the detection of malaria cells, aiding in medical diagnosis and research.
Myocardial Infraction Diagnosis using k-nearest neighbors algorithm (k-NN).
Early detection of Autism Spectrum Disorder (ASD) is crucial for children's development, yet the diagnostic procedure remains challenging. EyeTism employs machine learning on eye tracking data from both high-functioning ASD and typically developing children (TD) to create a diagnostic tool based on their distinct visual attention patterns.
Medical Diagnosis using Contrastive Learning
Machine Learning Model for predicting Heart Disease
Creating a Model that can diagnose pneumonia with an xray image
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