Abstract: One or more example embodiments relates to a computer-implemented method for determining a similarity measure, the similarity measure describing a similarity between a first patient and a second patient. The method includes receiving a first patient data record, wherein the first patient data record is assigned to the first patient; receiving a second patient data record, wherein the second patient data record is assigned to the second patient; receiving or determining a medical ontology, wherein the medical ontology is independent of the first patient data record and the second patient data record; determining a patient ontology based on the medical ontology and at least one of the first patient data record or the second patient data record; and determining the similarity measure based on the patient ontology.

Abstract: A computer-implemented method is for creating an individual gene panel plan. The method includes receiving and/or determining a plurality of clinical trials. In this case, each clinical trial of the plurality of clinical trials includes a molecular genetic inclusion criterion. The molecular genetic inclusion criterion relates in this case to gene information relevant to the respective clinical trial. The method further includes determining, for each clinical trial of the plurality of clinical trials, at least one genomic region to which the gene information of the clinical trial relates. The method further includes creating the gene panel plan based on the genomic regions determined in respect of the plurality of clinical trials. The method further includes providing the gene panel plan.

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 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 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.