Dynamic Multi-Swarm Particle Swarm Optimization Support Vector Machine

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.

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.

Code to run experiments generating synthetic time series medical data

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.

📊 Medical data analysis Python project

A MATLAB-based domain adaptation toolbox for medical data analysis. It supports synthetic data generation for rapid validation and benchmarking, and includes a collection of popular, lightweight domain adaptation algorithms. The toolbox also provides image-level domain adaptation (harmonization) methods for medical imaging applications.

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

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

Computing a Likelihood Ratio Test on Wisconsin Breast Cancer Dataset to detect the most relevant features to infer wether a tumor is Malignous or Benign

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.

A comprehensive healthcare data and medical image processing application for managing patient health data, analyzing biomedical signals, processing medical images, and creating interactive visualizations.

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.

Chronic Kidney Disease Prediction Using ML | Website |

Interpretation-focused analysis of 30-day ICU readmission using the MIMIC-III clinical database, with emphasis on cohort definition, data preprocessing, and clinical context.

FreeCodeCamp data analysis challenge: Medical Data Visualizer 📊