💻 Next Generation Healthcare: A Deep Learning Approach
- 2 mins💻 Next Generation Healthcare: A Deep Learning Approach
Institution: Technical University of Munich, Munich, Bavaria, Germany 📍 Duration: October 2022 - March 2023 (6 months) ⏳
🌐 Project Background
Diabetes is a rapidly growing health crisis, affecting approximately 8.5 million adults in Germany in 2022, with a significant increase predicted for the coming decades. Diabetes complications such as macrovascular events, including stroke and myocardial infarction, not only affect the quality and length of life, but also have a profound economic impact on healthcare systems and the German statutory health insurance system.
Recognising this challenge, targeted screening of patients at high risk of complications may prove more effective and cost efficient than routine screening. The use of routine data, which is ubiquitous and often under-utilised, opens up considerable potential for the development of new approaches to healthcare. The aim of our project was to use a large dataset from an insurance company to develop and evaluate predictive models for stroke and myocardial infarction in patients with type 2 diabetes.
🤖 Deep Learning: An Exploratory Subproject
Going beyond traditional regression and conventional machine learning approaches such as penalised logistic regression models, gradient boosting and random forest used in the parent project Moving to Next Generation Healthcare (MNGHC-ML), our sub-project (MNGHC-DL) proposed a deep learning approach. Deep learning networks learn by detecting intricate patterns in the data, representing the data at multiple levels of abstraction by constructing computational models consisting of multiple layers of processing.
🚀 Accomplishments and skills.
As a statistical consultant, I successfully implemented and evaluated a deep learning algorithm for predicting stroke and myocardial infarction in claims data of diabetes patients. Our team then published a research and analysis paper to contribute our findings to the wider scientific community.
This project involved using a range of skills including statistical modelling, statistical consulting, PyTorch, AI, data modelling, Jupyter, scientific writing, TensorFlow, biostatistics, scientific analysis, machine learning, statistics, Python, deep learning and R.
📌 Next steps and future developments
The analysis plan of our project “Moving to Next Generation Healthcare: A Deep Learning Approach” (MNGHC-DL) by Bajramovic, Schosser et al., 2022, is available here. We are currently working on the full text of our paper and I am excited to announce that it will be published soon! Stay tuned for our future developments! 🎉
Medina Bajramovic
Data Scientist and Biostatistician