JupyterLabs

AI-Powered Disease Detection on X-ray Images

The goal of this project was to develop a Deep Learning powered solution detecting a disease on medical X-ray images. The model I have developed achieved AUC of 0.98. The solution is part of a bigger system which is developed to assist medical doctors in their daily work.

Machine Learning Based Investment Strategy

The goal of this project was to develop a machine learning backed investment strategy based on multiple binary positive and negative signals sourced from price, market, and environment analysis. The strategy I have developed performed 4x better than the baseline.

Ischemic Stroke Risk Assessment

The goal of this project was to develop an AI backend engine for an intelligent decision support system which asses an ischemic stroke risk. The system was developed in collaboration with a health insurer to allow preventive interventions for patients with high risk of a stroke.

Predicting Blood Transfusion Needs

The goal of this project was to develop an AI-backed decision support system helping medical doctors to decide about blood transfusion. In collaboration with multiple hospitals we collected historical data about blood transfusions, patients, and medical tests relevant to blood transfusion.

Machine Learnin backed FAQ Chatbot

The goal of this project was to develop an AI backend for a frequently asked questions chatbot. A client had collected significant amount of questions and answers that were used to train machine learning natural language processing models.

Anomaly Detection in BI Smart Metrics

The goal of this project was to develop an anomaly detection pipeline for business intelligence systems in order to trigger a BI report distribution - via slack or e-mail - when an anomalous situation was detected or send an alert to predefined groups of managers.