The TOP Framework enables users to model phenotypes according to the Core Ontology of Phenotypes. It also includes a custom reasoning engine and query service for classification of individual data and searching in data repositories (e.g., Health Data Stores).
Age-stratified numbers of COVID-19 testpositives and deaths
This work was done as part of the NFDI4Health Task Force COVID-19 (nfdi4health.de). We gratefully acknowledge the financial support of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Number 451265285.
Introduction On this homepage we provide a web-based tool to calculate prognostic scores on haematopoietic toxicity for 6 cycles CHOP-like regimen in patients with aggressive NHL. As we used for this analysis the data collected within the NHL-B1 and NHL-B2 trials of the DSHNHL as described in detail in Pfreundschuh et al. the predictions are valid for similar patient populations.
Description We offer two types of models. Pre-treatment models include beside the therapy regimen only prognostic ...
Large scale epidemiological studies, such as LIFE-ADULT, including thousands of participants with a multitude of novel QT assessments allow to define reference values. Reference values are typically used in quality control to find outliers in a specified data volume or to evaluate a given measurement value regarding its pathologic value. Measuring the hand grip strength is a standard assessment in LIFE, for which is no or little prior knowledge regarding reference values available.
Based on the ...
Implementation of recently developed dynamic mathematical models of normal and leukemic hematopoiesis to practically impact clinical decision- making.
Fitting available individual patients information, prediction of next-cycle thrombopenia caused by CHOEP treatment based on the individual fits of the preceeding treatment cycles, changing next-cycle relative dosing, posponement of the next cycle, changing follow-up period, visualization of data and simulation
This package should simplify the translation of the classifications reported in Wichmann et al. 2015 to other data sets of head and neck cancers.
Classification of head and neck tumor samples into HPV-positive and negative samples based on their gene expression. Classification of the samples into molecular subgroups reported in Wichmann et al. 2015