dilaratank / msc-smallprojects

A collection of small projects from my Master's Medical Informatics (University of Amsterdam)

MSc-smallprojects

A collection of small projects from my Master's Medical Informatics (University of Amsterdam)

Data science medicine

• Data science: an assignment about data (pre)processing
• Regression and Prediction: training a multivariate regression model with risk factors of CVD to predict a CVD event
• SVM and Random Forest: Comparing the performance of SVM and RF and a NN on a simulatedConcentrations dataset
• Prediction Models (in R): Train prediction models on the BreastCancer dataset, also contains bootstrapping, AUC & NRI, StepAIC.

Data analysis medicine

• Mathematical Statistics: calculate the cost-efficacy ratio of a dataset and its 95% confidence interval, as well as a mathematical proof for the variance.
• Renal Transplantation (in R): Cox regression analysis to predict graft failure.
• Aorta Diameter Growth (in R): Mixed-effects regression model showing predictions with new data (new patients and new time points).
• Kidney Transplant (in R): Joining a cox regression model and a LME model for predictive value of repeated measures for graft and patient failure.

Reasoning with Health Data

The goal of this project is to get familiar with FAIR's principles about data. In order to do this, we came up with a project that will explore two data sources to make a claim about the correlation between BMI and AFib prevalence worldwide.

Biomedical Information System Engineering

PWA app: https://github.com/aespogom/NutriMobileApp