University of Zurich & University Hospital Zurich
$ health = f(data) $
Today, in every aspect of our lives, everything we do leaves a digital footprint. Health-care institutions are also increasingly …
We are proud to be part of the UZH University Research Priority Programs (URPP) where we with the Schwank lab investigate the use of AI …
Since the early days of computing, healthcare professionals have dreamt of using the vast storage and processing powers of computers to …
Comparing neural-networks versus logistic regression for predicting readmission.
Novel computational method for drug-drug interaction predictions which are an important consideration for patient treatment.
Here we perform an extensive analysis of adenine- and cytosine base editors on a library of 28,294 lentivirally integrated genetic sequences and establish BE-DICT, an attention-based deep learning algorithm capable of predicting base editing outcomes with high accuracy.
We propose a Siamese self-attention multi-modal neural network for Drug-drug interaction (DDI) prediction that integrates multiple drug similarity measures that have been derived from a comparison of drug characteristics including drug targets, pathways and gene expression profiles.
We investigated Talimogene laherparepvec (T-VEC) and its effect on the clinical, histological, single-cell transcriptomic and immune repertoire level using repeated fine-needle aspirates (FNAs) of injected and noninjected lesions in primary cutaneous B-cell lymphoma (pCBCL).
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.
In this review, we provide a comprehensive overview of the tools and methods that are used in patient similarity analysis with longitudinal data and discuss its potential for improving clinical decision making.
Clinical Data Science, Translational Bioinformatics, Cancer Genetics
Bioinformatics, Cancer Genomics, Long-read sequencing, cfDNA sequencing
NLP, Machine Learning, Information Extraction, Domain Adaptation
Finding solutions for biology motivated problems from an engineering point of view, Leveraging ICT for medicine, IoT & Smart Sensors
Time series analysis, Bayesian inference, Machine learning, Decision support systems for healthcare
Bioinformatics, Computational Pharmacology, Deep Learning
Bioinformatics, Cancer Genomics
Data Science Tooling, Reproducibility, Machine Learning
Data Science Tooling, Statistics, Machine Learning
Data Science, Human Disease Monitoring, IoT & Smart Sensors
Epidemiology, Biostatistics, Machine Learning for Health Care, Internal Medicine
Internal Medicine, Health Economics, Machine Learning in Health Care
Bioinformatics, Applied Mathematics, Genomics & Epigenetics, Algorithms
Physiology and Pathophysiology, Nonlinear Dynamics, Mechanistic Modelling
Machine Learning, NLP, Image Processing
Bioinformatics, Molecular biology
Artificial Intelligence, Causal Inference
Machine Learning for Health Care
Bioinformatics, Machine learning
Sleeping, Hunting birds and mice, Scratching trees
Jumping all over the place 🦘, Knocking over Chess pieces ♟️♕, remote control 📺 and everything in front of him, Playing soccer ⚽ and chasing butterflies 🦋, Sleeping 😴 in front of laptops 💻, Participating in origami 📄🏮 and crafting activities 🧶🎨
Kinematics of toy mice, Hiding in cardboard boxes
Fluid dynamics, Burrowing under blankets
Belly rubs, Staying at home, Hanging around with her dog