Abstract: A computer-implemented data protection method comprising: receiving an input dataset, the input dataset including a plurality of datapoints, at least some of the plurality of datapoints including information usable in combination to identify a patient; performing multivariate outlier detection on the input dataset, the performing including computing anomaly scores for at least a portion of the plurality of datapoints using a multivariate outlier detection algorithm; and identifying, based on the anomaly scores, at least one set of multivariate outliers of datapoints usable in combination to identify the patient.

Abstract: Systems and methods are provided for reliable individual readmission risk prediction. Information about an admitted patient is acquired. A model inputs the patient information and outputs a time-varying readmission risk prediction. The time-varying readmission risk prediction is presented in a relation to the Length of Stay (LoS) and the costs (actual costs and cost coverage). A treatment and/or discharge plan is generated that is implemented when a threshold risk is met.

Abstract: A computer-implemented method for determining a predictive disease status of an inflammatory disease of a patient is compatible with a system including a remote platform and at least one mobile user device, wherein the at least one mobile user device is associated with the patient and is in data communication with the platform. The method comprises: receiving, at the platform, monitoring data indicative of the health state of the patient from the user device associated to the patient; determining, at the platform, a predictive disease state of the inflammatory disease of the patient based on the received monitoring data; evaluating the determined predictive disease status; providing the predictive disease status to a user at the platform and/or the patient at the user device based on the evaluating the determined predictive disease status.

Abstract: A clinical decision support system for estimating drug-related treatment optimization concerning inflammatory diseases, comprises: a computing unit configured to host a plurality of prediction models, the computing unit including an input interface designed for receiving input data and an output interface designed to output result; a plurality of different trained prediction models, each model trained to predict the probability of treatment outcomes for a number of different drug-related treatment options and for a specific patient-group; a selection unit configured to automatically select one a prediction model depending on the input data according to a predefined selection scheme. The clinical decision support system is configured to produce output results by processing the input data with the selected prediction model.

Abstract: A plastic film of a thermoplastic synthetic resin is made in a film-making system by extrusion from a die of an extruder. First the plastic is melted and extruded from the die as a tube or web that is, typically after cooling and stretching, formed into a package. At least one reference parameter is provided, and, during continuous operation of the system, two input parameters different from the reference parameter are measured by respective measuring devices An output is determined from these reference parameters and is compared with the reference parameter.

Abstract: A system for making a nonwoven nonwoven spun-bond or melt-blown fabric has a spinneret for spinning fibers or filaments, a cooler downstream of the spinneret for cooling the spun fibers or filaments, a stretcher downstream of the cooler for stretching the cooled fibers or filaments, and a conveyor downstream of the stretcher. The stretched and cooled fibers or filaments are deposited as a nonwoven web on the conveyor. Sensors measure input parameters at the spinneret, at the cooler, at the stretcher, and/or at at least one diffuser or at the conveyor. An evaluating unit for determining an output parameter from the measured input parameter with respect to a predetermined reference parameter.

Abstract: Methods and apparatuses are for a medical dataset stored locally within a first facility and including a number of original individual datasets assigned to real existing patients and including original values for one or more higher-ranking variables. An embodiment of the method includes creation of a synthetic dataset based on the medical dataset, the synthetic dataset including a number of synthetic individual datasets including synthetic values for the same higher-ranking variables as the medical dataset, not relatable to an original existing patient, the creation being undertaken locally within the first facility by application of a sampling function to the medical data; and transfer of the synthetic dataset from the first facility to a central unit outside the first facility. The synthetic dataset is utilizable within the central unit.

Abstract: A plastic-extrusion system comprises a plurality of system components including an extruder and a collection device for collecting the extruded plastic material. The plastic-extrusion system has an operator station designed for taking in and outputting data of the plastic-extrusion system. The operator station further has a mobile terminal including a screen of a graphical user interface as well as a camera. The plastic-extrusion system is associated with at least one information source, and preferably a plurality of information sources. The operator station is configured so as to provide access to the at least one information source, and preferably to the plurality of information sources.

Abstract: A computer-implemented method for client-specific federated learning is disclosed applicable in a system including a central server unit and a plurality of client units. The client units are respectively located at different local sites and respectively include local data which is subject to data privacy regulations. In an embodiment, the method includes providing, to one or more of the client units, a toolset, the toolset being configured such that a plurality of different machine learned models can be derived from the toolset at the one or more client units. It further includes receiving, from the one or more client units, one or more machine learned models, the one or more machine learned models being respectively derived from the toolset and trained based and the respective local data by the client units. Finally, the method includes storing the one or more machine learned models in the central server unit.

Abstract: The invention relates to various aspects in the production of extrusion products. The properties of extruded articles are dependent significantly, in addition to their formulation, also on the setting variables and in particular on the thus resulting process variables. The setting variables and in particular the process variables thus represent a state of the extrusion process characterized as “fingerprint”. The thus claimed invention takes into account these facts and supports the operator of a production plant to detect earlier changes in quality and to systematically counteract a deterioration in the quality.

Abstract: A method is for creating predictive models for an automated clinical decision support system for automated supervised and semi-supervised classification and treatment optimization of clinical events, e.g. of disease activity in autoimmune diseases, using EMR data and predictive models in a nested cross validation, as well as a respective prediction-unit for creating prediction-data for an automated clinical decision support system. Another method is for automated clinical decision support for automated supervised and semi-supervised classification and treatment optimization of clinical events using EMR data, as well as a respective decision support system.

Abstract: The invention relates to various aspects in the production and further processing of plastic sheet material, in particular a spun-bonded non-woven fabric, a melt-blown non-woven fabric, a composite non-woven fabric, a blown film, a flat film, a plastic board or a plastic panel. A core aspect in the value chain of sheet material is a method and device for providing, retrieving and using a data element for exchanging in an over-lapping step-wise manner, a plurality of different data elements for producing the end product within the value chain of the sheet material. Within the value chain, it is possible to optimize the method using said data, to improve the construction of the used machines and systems and to improve the system technology as well as method technology for producing the sheet material.

Abstract: Methods for constructing classifiers for binary classification of quantitative brain electrical activity data is described. The classifier building methods are based on the application of one or more evolutionary algorithms. In one embodiment, the evolutionary algorithm used is a genetic algorithm. In another embodiment, the evolutionary algorithm used is a modified Random Mutation Hill Climbing algorithm. In yet another embodiment, a combination of a genetic algorithm and a modified Random Mutation Hill Climbing algorithm is used for building a classifier. The classifier building methods are fully automated, and are adapted to generate classifiers (for example, Linear Discriminant Functions) with high sensitivity, specificity and classification accuracy.

Abstract: A plastic film of a thermoplastic synthetic resin is made in a film-making system by extrusion from a die of an extruder. First the plastic is melted and extruded from the die as a tube or web that is, typically after cooling and stretching, formed into a package. At least one reference parameter is provided, and, during continuous operation of the system, two input parameters different from the reference parameter are measured by respective measuring devices An output is determined from these reference parameters and is compared with the reference parameter.

Abstract: A plastic-extrusion system comprises a plurality of system components including an extruder and a collection device for collecting the extruded plastic material. The plastic-extrusion system has an operator station designed for taking in and outputting data of the plastic-extrusion system. The operator station further has a mobile terminal including a screen of a graphical user interface as well as a camera. The plastic-extrusion system is associated with at least one information source, and preferably a plurality of information sources. The operator station is configured so as to provide access to the at least one information source, and preferably to the plurality of information sources.

Abstract: A system for making a nonwoven nonwoven spun-bond or melt-blown fabric has a spinneret for spinning fibers or filaments, a cooler downstream of the spinneret for cooling the spun fibers or filaments, a stretcher downstream of the cooler for stretching the cooled fibers or filaments, and a conveyor downstream of the stretcher. The stretched and cooled fibers or filaments are deposited as a nonwoven web on the conveyor. Sensors measure input parameters at the spinneret, at the cooler, at the stretcher, and/or at at least one diffuser or at the conveyor. An evaluating unit for determining an output parameter from the measured input parameter with respect to a predetermined reference parameter.

Abstract: Methods for constructing classifiers for binary classification of quantitative brain electrical activity data is described. The classifier building methods are based on the application of one or more evolutionary algorithms. In one embodiment, the evolutionary algorithm used is a genetic algorithm. In another embodiment, the evolutionary algorithm used is a modified Random Mutation Hill Climbing algorithm. In yet another embodiment, a combination of a genetic algorithm and a modified Random Mutation Hill Climbing algorithm is used for building a classifier. The classifier building methods are fully automated, and are adapted to generate classifiers (for example, Linear Discriminant Functions) with high sensitivity, specificity and classification accuracy.