Patrick Styll's Projects
The goal of this project is to implement a BERT-based architecture to successfully extract diseases and medical conidtions from free-text.
A pipeline that extracts multiple medical entities from patient admission notes, maps them to their respective ICD/NDC code and outputs a standardized FHIR structure.
Experiments with interpreting techniques, such as SHAP and LIME, to get insight into the trade-off between predictive performance and explainability.
Fun project with the goal of classifying fruits in real time through a convolutional neural network.
The global pairwise sequence alignment algorithm is a bioinformatics method that aligns two sequences from start to finish to identify the optimal sequence alignment based on predefined scoring parameters. Fun example of Parallelization with OpenMP.
The goal is to perform grouped Independent Component Analysis (ICA) to extract meaningful signals from neonatal brains via the developing Human Connectome Project (dHCP). These Independent Components are planned to be used as an input for SwiFUN, to extract task-related information from resting-state functional Magnetic Resonance Images (rsfMRI).
This repository serves to contain my submissions for my participation at MultiCardioNER 2024.
The aim is to train an advanced NLP model that can efficiently and accurately extract relevant diagnoses and diseases from admission notes. The dataset containing pseudonymized admission notes is publicly available here: http://trec-cds.org/topics2021.xml
This project is aimed to experiment with various Deep Learning architectures for Natural Language Processing.
Official repo for SwiFUN