A ready-to-use framework of the state-of-the-art models for structured (tabular) data learning with PyTorch. Applications include recommendation, CRT prediction, healthcare analytics, anomaly detection, and etc.

A web application that assists patients with reviewing objective quality indicators and subjective reviews together along with making an informed decision about their future care.

Humana-Mays Healthcare Analytics 2020 Case Competition

A project using Python's PyML library to predict whether an employee needs mental health treatment or not based on their background data acquired from their survey answers

[3rd Place DevSC] Telegram Chatbot POC for the Brazilian Healthcare System

Uncover the revolutionary impact of handwashing on mortality rates in healthcare. Explore the story of Dr. Semmelweis and his groundbreaking findings.

Streaming ETL data pipeline for health event monitoring and predictive analytics using Kafka, Airflow, Docker, Hadoop and Spark ML.

This project aims to create a deep learning based model for the segmentation of brain tumours and their subregions from MRI scans, as well as the prediction of patient survival . The segmentation is performed using a U-Net architecture, while survival prediction is done using CNN models.

Machine Learning project using Logistic Regression to predict the likelihood of diabetes based on health parameters. Includes EDA, preprocessing, model training, and evaluation.

All my web files for Tucson Health Insurance Solutions

A comprehensive platform for analyzing local health data with ETL pipelines, data visualization, and predictive analytics. Includes integration with APIs and Power BI dashboards for actionable insights.

Python Streamlit app for generating synthetic ED visits data. Use cases: data portfolio projects, testing/validation of healthcare analytics scripts, personal learning.

Predicting patient outcomes is a crucial task in healthcare that can have a significant impact on improving patient care.

AI-powered chatbot using Retrieval-Augmented Generation (RAG) to provide reliable answers to healthcare-related questions.

A program that calculates the hourly patient census in a hospital emergency department or inpatient unit, as well as the hourly staffing, and produces a common dataset that can be used for analysis.