A real-time data cleaning pipeline for medical and healthcare data using Apache Spark, SparkNLP, Spark Streaming, and Kafka.

A Python bootcamp for medical students designed to teach basic DICOM and imaging data handling skills.

Code to run experiments generating synthetic time series medical data

This project uses Python to process electrocardiogram (ECG or EKG) signals and calculate heart rate (HR) through biomedical signal processing techniques. It includes noise filtering and R-peak detection for accurate HR analysis. The project features a user-friendly graphical interface to visualize ECG data and heart rate results.

📊 Medical data analysis Python project

A deep learning model to predict blood donor availability using TensorFlow and sklearn. Features data preprocessing, neural network training, and ROC curve visualization. Achieve high accuracy in predicting donor status! 🩺💉

Predict Diabetes Progression: A linear regression model to predict diabetes progression using patient attributes. Collaborate to improve predictions. Jupyter Notebook implementation.

Pymimic3 is a scalable experimentation platform for MIMIC-III, featuring ready-to-run models, fully tested utilities for concept drift research, and a parallelized, configurable data pipeline.

Aplicación para el seguimiento de la presión arterial, permitiendo el registro y visualización de mediciones de presión sistólica y diastólica.

A web application that detects gender bias in healthcare datasets, enabling equitable AI-driven care and supporting the advancement of inclusive data informed medical research.

Package to develop and evaluate time series data models based on fluctuation based clustering and Earth Mover's Distances

Chronic Kidney Disease Prediction Using ML | Website |

Machine learning pipeline for predicting postoperative outcomes in adult male circumcision using Milan Clinic data, with full preprocessing, modeling, evaluation, and explainability.

We will explore a data set dedicated to the cost of treatment of different patients. The cost of treatment depends on many factors: diagnosis, type of clinic, city of residence, age and so on.

create barplot and heatmap

PyTorch-based deep learning model designed to predict diabetes outcomes using the Diabetes Dataset. The neural network utilizes Leaky ReLU activations and dropout for improved model performance and generalization.

Comprehensive pipeline for medical insurance cost prediction featuring data inspection, visualization, and regression modeling (linear, polynomial, random forest) on personal and health records.

MedSummarize AI Medical research assistant that extracts and simplifies complex articles for doctors and patients. 🔍 Features: Dual-mode summaries (expert/patient) Medical term & relationship extraction PubMed-optimized processing Interactive Q&A For: Researchers, doctors.

Applied Data Science in Medicine and Psychology