Data Science

A Quest for Reproducible Data Science

Have you ever tried to reproduce someone else’s analysis and got different results?

AutoDiscern: Rating the Quality of Online Health Information with Hierarchical Encoder Attention-based Neural Networks

To help patients find high quality health information online, we developed a Deep Learning system that evaluates the quality of online health articles. The system implements the DISCERN criteria, which checks for references, balanced writing, and more.

30 days All-Cause Readmission

Comparing neural-networks versus logistic regression for predicting readmission.

autoDISCERN

Assessing the quality of online health information with AI.

Drug-Drug Interactions

Novel computational method for drug-drug interaction predictions which are an important consideration for patient treatment.

Automated Reports from Xrays

Using deep learning for automatically generated medical reports describing radiological images.

Neural networks versus Logistic regression for 30 days all-cause readmission prediction

We conclude that data from patient timelines improve 30 day readmission prediction, that a logistic regression with LASSO has equal performance to the best neural network model and that the use of administrative data result in competitive performance compared to published approaches based on richer clinical datasets.

We are looking for Masters Students!

We are currently looking for Master’s students in the field of bioinformatics for the following topics Data integration in Cancer Genomics The project’s aim is to characterize the effects of transcriptional and epigenetic processes on mutational patterns in cancer. The student should have basic experience with Unix systems and some experience with at least one scripting language (e.g. Python, R or bash). Prior experience with genomics software (mappers, samtools or variant callers) is an advantage.