Abstract: A method for predicting health status of a subject, including: receiving at least one subject-related dynamic property data, receiving at least one subject-related covariate, processing the at least one subject-related dynamic property data and the at least one subject-related covariate data to generate a subject-related processed dataset, generating at least one health status hypothesis based on the subject-related processed dataset, and predicting at least one health status based on the at least one health status hypothesis. Also described is a system that can execute the method for predicting health status of a subject, including: at least one processing component; and at least one analyzing component, wherein the system is configured to predict at least one health status based on the at least one health status hypothesis.

Abstract: The present invention a system and a method for monitoring young children comprising a plurality of sensors (1-5) providing signals that are configured to be converted into sensor data and a management component (10-26) configured for receiving the sensor data and for managing a health status and or disease progression on the basis of a model. The management component can comprise a prediction component for predicting the health status on the basis of a model. The method comprises a respective prediction step. The management component can be further configured to compute at least one of health data from a health data base, individual data from a storage and/or genetic data from a genetic data base. The plurality of sensors can be configured to be attached or applied to a young child and/or its mother. The model can be a trained model that can be further trained and adjusted on the basis of the data gained.

Abstract: The invention relates to a method for the production of templated carrier particles with primary and secondary internal structures comprising the steps of a) combining a carrier material with a template material, wherein the carrier material forms primary structures and secondary internal structures; b) transforming the template material; c) removing the transformed template material; and d) obtaining carrier particles with secondary internal structures. Further, the invention relates to a carrier particle with secondary internal structures obtainable by the method according to the invention. The method of the invention can further be used for the production of a compacted carrier matter, by further comprising a step of compacting the carrier particles with secondary internal structures to obtain the compacted carrier matter.

Abstract: The present description relates to a method for automatically determining an optimal individual dosing regimen of at least one drug. The method includes providing a mathematical model adapted to model a progression of said disease and an effect of the at least one drug on the progression of the disease, the model comprising individual model parameters associated with the patient. The method includes utilizing an empirical Bayesian estimation to automatically and numerically estimate the individual model parameters of the mathematical model. The method includes automatically calculating an optimal individual dosing regimen for the mathematical model by solving an optimal control problem based on a desired progression of the disease, the estimated individual model parameters, and an initial guess for the dosing regimen. The method includes adjusting the optimal individual dosing regimen to optionally account for at least one clinical constraint to yield the optimal individual dosing regimen.

Abstract: The present invention relates to a method for predicting health status of a subject, the method comprising: receiving at least one subject-related dynamic property data, receiving at least one subject-related covariate, processing the at least one subject-related dynamic property data and the at least one subject-related covariate data to generate a subject-related processed dataset, generating at least one health status hypothesis based on the subject-related processed dataset, and predicting at least one health status based on the at least one health status hypothesis.

Abstract: The invention relates to a method and a computer program for estimating a bilirubin level of a neonate, composed of the steps of: Acquiring a series of bilirubin levels estimated at different time points from a sample obtained from a neonate, Acquiring a plurality of covariates from the neonate, each composed of an information about a neonatal property, Providing a pre-defined bilirubin model function, wherein the bilirubin model function is configured to describe a time course of a bilirubin level of a neonate, Determining a plurality of model parameters of the bilirubin model function, wherein each model parameter is estimated from at least one covariate of the plurality of covariates and an associated population model parameter, Determining from the series of acquired bilirubin levels and the bilirubin model function with the determined model parameters an expected bilirubin level of the neonate for a time particularly later than a lastly acquired bilirubin level of the series of bilirubin levels.

Abstract: The invention relates to a method and a computer program for estimating a bilirubin level of a neonate, composed of the steps of: Acquiring a series of bilirubin levels estimated at different time points from a sample obtained from a neonate, Acquiring a plurality of covariates from the neonate, each composed of an information about a neonatal property, Providing a pre-defined bilirubin model function, wherein the bilirubin model function is configured to describe a time course of a bilirubin level of a neonate, Determining a plurality of model parameters of the bilirubin model function, wherein each model parameter is estimated from at least one covariate of the plurality of covariates and an associated population model parameter, Determining from the series of acquired bilirubin levels and the bilirubin model function with the determined model parameters an expected bilirubin level of the neonate for a time particularly later than a lastly acquired bilirubin level of the series of bilirubin levels.

Abstract: The invention relates to a method and a computer program for estimating a bilirubin level of a neonate, comprising the steps of: Acquiring a series of bilirubin levels estimated at different time points from a sample obtained from a neonate, Acquiring a plurality of covariates from the neonate, each comprising an information about a neonatal property, Providing a pre-defined bilirubin model function, wherein the bilirubin model function is configured to describe a time course of a bilirubin level of a neonate, —Determining a plurality of model parameters of the bilirubin model function, wherein each model parameter is estimated from at least one covariate of the plurality of covariates and an associated population model parameter, Determining from the series of acquired bilirubin levels and the bilirubin model function with the determined model parameters an expected bilirubin level of the neonate for a time particularly later than a lastly acquired bilirubin level of the series of bilirubin levels.

Abstract: The invention relates to methods for estimating a bilirubin level of a neonate, comprising the steps of acquiring a series of bilirubin levels estimated at different time points from a sample obtained from a neonate; acquiring a plurality of covariates from the neonate, each comprising an information about a neonatal property; providing a pre-defined bilirubin model function; determining a plurality of model parameters of the bilirubin model function; and determining from the series of acquired bilirubin levels and the bilirubin model function with the determined model parameters an expected bilirubin level of the neonate for a time particularly later than a lastly acquired bilirubin level of the series of bilirubin levels.