Abstract: A method for providing a secondary parameter, a decision support system, a computer-readable medium and a computer program product are disclosed. In an embodiment, the method is for providing a secondary parameter in a decision support system providing a primary parameter, in particular in a clinical decision support system. The method includes: providing an input data set; approximating a secondary parameter based on the input data set by using a sub-system being trained by a machine learning mechanism, in particular by a deep learning mechanism; and providing the approximated secondary parameter. The input data set is a shape data set.

Abstract: Techniques for processing one or more frames of an angiogram are disclosed. The processing may take place during or after an angiography exam. The one or more frames of the angiogram are acquired during the angiography exam. The one or more frames are processed to determine, based on at least one pre-defined criterion, whether the angiogram at least comprises one frame with a diagnostic value among the one or more frames. If the angiogram comprises at least one frame with the diagnostic value, based on the angiogram, a score quantifying the diagnostic value of the angiogram is determined using a trained machine-learning (ML) algorithm. Techniques for processing, e.g., ranking/sorting, multiple angiograms associated with an anatomical region of interest of a patient are also provided, by which a respective score for each of the multiple angiograms is determined using the techniques for processing one or more frames of an angiogram.

Abstract: In a computer-implemented method, a machine-learning model is pre-trained in an unsupervised manner to predict time-related information based on data obtained from a contrast-enhanced medical imaging measurement. This pre-trained machine-learning model is then used to build another machine-learning model to predict semantic context information for images determined from the contrast-enhanced medical imaging measurement.

Abstract: Angiography angles are determined. Patient information and target vessel information are obtained, wherein the patient information defines individual medical information of a patient and wherein the target vessel information defines at least one target vessel to be imaged. At least one angiography angle is determined based on the patient information and the target vessel information. Angiograms obtained using the at least one angiography angle are analyzed to determine a vessel coverage of the target vessel and based on the vessel coverage determines additional angiography angles.

Abstract: A system is for infectious disease notification. The system includes at least one processor, configured to use a machine learning monitoring algorithm, trained on a large number of EMR datasets of patients, to calculate a probability for an infectious disease from a provided EMR dataset and compare the probability of the provided EMR dataset calculated with a known value. In training of the monitoring algorithm, the value represents whether there was an onset of an infectious disease or not and the monitoring algorithm is designed to adjust parameters of the monitoring algorithm. And in evaluating a notification, the value is a threshold value and the system is designed to output a notification upon the probability being greater than the threshold value.

Abstract: One or more example embodiments of the present invention relates to a method for the automated determination of examination results in an image sequence from multiple chronologically consecutive frames, the method comprising determining diagnostic candidates in the form of contiguous image regions in the individual frames for a predefined diagnostic finding; and for a number of the diagnostic candidates, determining which candidate image regions in other frames correspond to the particular diagnostic candidate, determining whether the candidate image regions of the particular diagnostic candidate in the other frames overlap with other diagnostic candidates, generating a graph containing the determined diagnostic candidates of the frames as nodes and the determined overlaps as edges, and generating communities from nodes connected via edges.

Abstract: A method and a device are for exchanging information regarding the clinical implications genomic variations. In an embodiment, the method includes receiving login-data of a user; evaluating the login-data received; establishing an encrypted data connection to the user after the evaluating indicates a positive evaluation of the login-data; saving, upon receiving a dataset in a context of a genomic variation, the dataset received in a memory, context-related with the genomic variation; and evaluating, upon a user request being received and connected with a search query for the genomic variation, a set of datasets from the memory, the datasets being context-related with the genomic variation and the set including the datasets that the user is authorized to receive, and sending the set of datasets to the user.

Abstract: For robust view classification and measurement estimation in sequential ultrasound imaging, the classification and/or measurements for a given image or sequence of images are gated. To prevent oscillation in results, the gating provides consistent output.

Abstract: The invention describes a method for automatically localizing organ segments in a three-dimensional image comprising the following steps: providing a three-dimensional image showing at least one organ and at least one tubular network comprising a plurality of tubular structures, the organ comprising organ segments; performing automatic separation of the organ from other parts of the image; performing automatic tracing of the tubular network to obtain a branch map; performing automatic analysis of the branch map to identify specific tubular structures; performing automatically assigning regions of the organ to the specific tubular structures to segment the organ into localized organ segments; and outputting the localized organ segments and the traced and analyzed tubular network as image data. The invention further describes a localization arrangement and a medical imaging system.

Abstract: Intelligent multi-scale image parsing determines the optimal size of each observation by an artificial agent at a given point in time while searching for the anatomical landmark. The artificial agent begins searching image data with a coarse field-of-view and iteratively decreases the field-of-view to locate the anatomical landmark. After searching at a coarse field-of view, the artificial agent increases resolution to a finer field-of-view to analyze context and appearance factors to converge on the anatomical landmark. The artificial agent determines applicable context and appearance factors at each effective scale.

Abstract: A method of generating a first image from a medical text report comprises acquiring a medical text report comprising one or more natural language statements; analysing the medical text report, using a computer-implemented analysis process, to determine for each natural language statement whether the statement satisfies a predetermined criterion with respect to a first medical finding; and responsive to a determination that a said statement satisfies the predetermined criterion, adding an image representing the first medical finding to an image template, to generate the first image. Also disclosed is an apparatus and computer program.

Abstract: Systems and methods for mapping a patient to one or more clinical trials are provided. Patient data of a patient is received and encoded into a patient model of the patient. Synthetic patients are generated for each clinical trial in a set of clinical trials based on characteristics of participants in that clinical trial. The patient model of the patient is compared to each of the synthetic patients to identify synthetic patients matching the patient model. The patient is mapped to one or more clinical trials in the set of clinical trials based on the matching synthetic patients.

Abstract: Systems and methods are provided for evaluating an aorta of a patient. A medical image of an aorta of a patient is received. The aorta is segmented from the medical image. One or more measurement planes are identified on the segmented aorta. At least one measurement is calculated at each of the one or more measurement planes. The aorta of the patient is evaluated based on the at least one measurement calculated at each of the one or more measurement planes.

Abstract: A computer-implemented method is for providing quantitative airway information. In an embodiment, the method includes receiving and/or determining first medical image data of an airway segment; applying a first trained function to the first medical image data, to generate output data; determining the at least one quantitative airway information of the airway segment based on the output data; and providing the at least one quantitative airway information.

Abstract: An embodiment of a method includes providing a first result list indicating a plurality of first anatomic structures and indicating, for each respective first anatomic structure of the plurality of first anatomic structures, a corresponding first severity indicator; providing a second result list indicating, for each respective second anatomic structure of the plurality of the second anatomic structures, a corresponding second severity indicator; providing a relationship matrix indicating a level of interrelatedness between the first anatomic structures and the second anatomic structures; and generating, based on the first result list provided, on the second result list and on the relationship matrix provided, a concordance visualization indicating a respective level of concordance between at least one of the first anatomic structures and the corresponding first severity indicator, and indicating a respective level of concordance between at least one of the second anatomic structures and the corresponding sec

Abstract: A computer-implemented method for sharing medical information includes receiving a first genomic data set, the first genomic data set being generated at a first site; comparing the first genomic data sets with a plurality of second genomic data sets stored in a database external to the first site; and identifying, amongst the second genomic data sets, one or more reference genomic data sets, based upon determining a similarity between first genomic data set and one or more of the second genomic data sets. The method further includes dispatching a notification to the first site indicative of the one or more reference genomic data sets.

Abstract: A system operable to transmit healthcare data to a user device is provided. The system maintains data representing a first directed graph, representing at least part of a medical guideline, in a database and a plurality of patient models including healthcare data. An element is selected from the first directed graph by processing the models and the data. Based on a combination of the selected element and the plurality of patient models, a first and second patient cohort are identified, treatment of the first patient cohort having deviated from the at least part of a medical guideline at the selected element. At least one patient cohort characteristic distinguishing the first patient cohort from the second patient cohort is determined by processing the patient models. A second directed graph is generated, based on at least the at least one identified patient cohort characteristic, and transmitted for receipt by the user device.

Abstract: A system is for infectious disease notification. The system includes at least one processor, configured to use a machine learning monitoring algorithm, trained on a large number of EMR datasets of patients, to calculate a probability for an infectious disease from a provided EMR dataset and compare the probability of the provided EMR dataset calculated with a known value. In training of the monitoring algorithm, the value represents whether there was an onset of an infectious disease or not and the monitoring algorithm is designed to adjust parameters of the monitoring algorithm. And in evaluating a notification, the value is a threshold value and the system is designed to output a notification upon the probability being greater than the threshold value.

Abstract: A method and a device are for exchanging information regarding the clinical implications genomic variations. In an embodiment, the method includes receiving login-data of a user; evaluating the login-data received; establishing an encrypted data connection to the user after the evaluating indicates a positive evaluation of the login-data; saving, upon receiving a dataset in a context of a genomic variation, the dataset received in a memory, context-related with the genomic variation; and evaluating, upon a user request being received and connected with a search query for the genomic variation, a set of datasets from the memory, the datasets being context-related with the genomic variation and the set including the datasets that the user is authorized to receive, and sending the set of datasets to the user.

Abstract: A computer-implemented method and a system are for performing or supporting a medical task. An embodiment of the method includes obtaining a medical task and obtaining values for data fields of a number of available data fields. The method further includes determining whether an insufficient data field is present; and, if such a field is present, determining a relevance metric for the medical task, for the insufficient data field and/or the value thereof. Further, the method includes providing, via an estimator function, at least two different values for the insufficient data field; calculating at least two results for the medical task, which are based on the at least two different values provided; determining whether the relevance metric determined reaches or exceeds a relevance threshold value and, if this is the case, outputting an output signal based on the at least two results calculated.