Data Science

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.

Patient*innenperspektiven zur Akzeptanz und Nutzbarkeit digitaler Gesundheitstechnologien in der Onkologie - eine qualitative Studie

Digitale Werkzeuge wie Conversational Agents und Wearables bieten vielversprechende Möglichkeiten zur Erfassung von Patient-Reported Outcomes (PROs) und objektiven Krankheitsverläufen, wodurch das Wohlbefinden der Patientinnen verbessert werden kann und eine personalisierte Behandlung in der Onkologie ermöglicht wird. Die erfolgreiche Einführung und Umsetzung dieser Werkzeuge in herkömmlichen Gesundheitssystemen kann jedoch Herausforderungen mit sich bringen. Schlüsselfaktoren sind die Einbindung der Patientinnen, die Akzeptanz und die Anwendungsfreundlichkeit des Systems. Um diese entscheidenden Aspekte anzugehen, ist ein nutzungsorientrierter Ansatz unerlässlich, der sich darauf konzentriert, die Bedürfnisse der Patient*innen zu verstehen und technologiebedingte Barrieren zu überwinden.

Software development engineer 80 - 100 %

The LOOP Zurich is a medical center for translational research and precision medicine. It focuses on new approaches, better diagnostics, and novel therapies that will benefit patients and society as a whole. The goal is to enhance personalized healthcare by efficiently transferring scientific knowledge into medical practice. As part of its strategy, The LOOP Zurich is developing an IT research platform (“LOOP BMIP Data Platform”) between the major Zurich hospitals and academic partners (University of Zurich and ETHZ) of strategic importance to the Zurich medical research ecosystem.

We are looking for Master Students to work on Cost-effective Clinical Pathways!

We are currently looking for Master students interested to work on projects at the intersection of machine learning and medicine. Machine-Learning for the Identification of Cost-effective Clinical Pathways Do you want to combine state-of-the-art machine learning (ML) algorithms with the pressing societal problem of high (and rising) healthcare costs? Are you motivated to work with interesting real-world data and excited to implement and apply machine learning algorithms? High and rising healthcare costs are a significant challenge in many developed countries, which is expected to intensify with the demographic changes that will accelerate over the next decades.