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Combining graph neural networks and spatio-temporal disease models to improve the prediction of weekly COVID-19 cases in Germany.

Scientific reports
During 2020, the infection rate of COVID-19 has been investigated by many scholars from different research fields. In this context, reliable and interpretable forecasts of disease incidents are a vital tool for policymakers to manage healthcare resou...

Deep learning shows declining groundwater levels in Germany until 2100 due to climate change.

Nature communications
In this study we investigate how climate change will directly influence the groundwater resources in Germany during the 21 century. We apply a machine learning groundwater level prediction approach based on convolutional neural networks to 118 sites ...

Robotic-assisted Versus Laparoscopic Radical Prostatectomy: 12-month Outcomes of the Multicentre Randomised Controlled LAP-01 Trial.

European urology focus
BACKGROUND: Recently, our LAP-01 trial demonstrated superiority of robotic-assisted laparoscopic radical prostatectomy (RARP) over conventional laparoscopic radical prostatectomy (LRP) with respect to continence at 3 mo.

[The analysis of CIRSmedical.de using Natural Language Processing].

Zeitschrift fur Evidenz, Fortbildung und Qualitat im Gesundheitswesen
BACKGROUND: CIRSmedical.de is a publicly accessible, cross-institutional reporting and learning system, which is organized by the German Agency for Quality in Medicine (ÄZQ). CIRSmedical.de has existed since 2005 and has published more than 6,000 eve...

Deep learning for prediction of population health costs.

BMC medical informatics and decision making
BACKGROUND: Accurate prediction of healthcare costs is important for optimally managing health costs. However, methods leveraging the medical richness from data such as health insurance claims or electronic health records are missing.

Views on Using Social Robots in Professional Caregiving: Content Analysis of a Scenario Method Workshop.

Journal of medical Internet research
BACKGROUND: Interest in digital technologies in the health care sector is growing and can be a way to reduce the burden on professional caregivers while helping people to become more independent. Social robots are regarded as a special form of techno...

OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany.

PLoS computational biology
Mathematical models in epidemiology are an indispensable tool to determine the dynamics and important characteristics of infectious diseases. Apart from their scientific merit, these models are often used to inform political decisions and interventio...

Deep-learning-based synthesis of post-contrast T1-weighted MRI for tumour response assessment in neuro-oncology: a multicentre, retrospective cohort study.

The Lancet. Digital health
BACKGROUND: Gadolinium-based contrast agents (GBCAs) are widely used to enhance tissue contrast during MRI scans and play a crucial role in the management of patients with cancer. However, studies have shown gadolinium deposition in the brain after r...

[Digitization of the healthcare system: the BfArM's contribution to the development of potential].

Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz
Digitalization is a clear megatrend of our time, also in the health sector, which is currently experiencing enormous acceleration due to the COVID-19 pandemic in addition to paving the way due to changes in the legal framework. Looking to the future,...