BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix

SHEPHERD: Few shot learning for phenotype-driven diagnosis of patients with rare genetic diseases

Code for "Graph-Evolving Meta-Learning for Low-Resource Medical Dialogue Generation". [AAAI 2021]

A Vietnamese dataset of over 12 thousands questions about common disease symptoms. Perfect for researchers and developers building Vietnamese healthcare chatbots or disease prediction models.

A Deep Learning Based approach for diagnosis of Schizophrenia using EEG brain recordings

Medical image analysis tool to identify various diseases from MRIs, CT scans, X-Rays and more

"Worse than Random? An Embarrassingly Simple Probing Evaluation of Large Multimodal Models in Medical VQA"

Using TensorFlow Object Detection API to detect blood cells

Myocardial Infraction Diagnosis using k-nearest neighbors algorithm (k-NN).

This project aims to predict the presence of heart disease based on various medical attributes of an individual. It utilizes a logistic regression model trained on a dataset containing information about patients and whether they have heart disease or not.

Chronic Kidney Disease Prediction Using ML | Website |

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

Code for my Master Thesis project on "Prompting Techniques for Natural Language Generation in the Medical Domain" at the University of Bologna

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.

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.

Machine Learning Model for predicting Heart Disease