Octrooien

The present disclosure relates to secure broker-mediated data analysis and prediction. One example embodiment includes a method. The method includes receiving, by a managing computing device, a plurality of datasets from client computing devices. The method also includes computing, by the managing computing device, a shared representation based on a shared function having one or more shared parameters. Further, the method includes transmitting, by the managing computing device, the shared representation and other data to the client computing devices. In addition, the method includes, based on ...

The present disclosure relates to secure broker-mediated data analysis and prediction. One example embodiment includes a method. The method includes receiving, by a managing computing device, a plurality of datasets from client computing devices. The method also includes computing, by the managing computing device, a shared representation based on a shared function having one or more shared parameters. Further, the method includes transmitting, by the managing computing device, the shared representation and other data to the client computing devices. In addition, the method includes, based on ...

The present disclosure relates to secure broker-mediated data analysis and prediction. One example embodiment includes a method. The method includes receiving, by a managing computing device, a plurality of datasets from client computing devices. The method also includes computing, by the managing computing device, a shared representation based on a shared function having one or more shared parameters. Further, the method includes transmitting, by the managing computing device, the shared representation and other data to the client computing devices. In addition, the method includes, based on ...

The invention solves the problem of using machine learning to build a joint model from multiple training data sets, potentially belonging to multiple parties that may be geographically distributed, where no party can infer the training data set from any other party. The federated model trained on these multiple datasets has higher accuracy than models built from an individual dataset.

The invention solves the problem of using machine learning to build a joint model from multiple training data sets, potentially belonging to multiple parties that may be geographically distributed, where no party can infer the training data set from any other party. The federated model trained on these multiple datasets has higher accuracy than models built from an individual dataset.

The invention solves the problem of using machine learning to build a joint model from multiple training data sets, potentially belonging to multiple parties that may be geographically distributed, where no party can infer the training data set from any other party. The federated model trained on these multiple datasets has higher accuracy than models built from an individual dataset.

The invention solves the problem of using machine learning to build a joint model from multiple training data sets, potentially belonging to multiple parties that may be geographically distributed, where no party can infer the training data set from any other party. The federated model trained on these multiple datasets has higher accuracy than models built from an individual dataset.

Provided is a training method (100) for training a predictive model, PM, (132) for highlighting cellular objects, c-objects, in a test Brightfield, BF, image of a test sample (202) of one or more c-objects acquired using a test microscope (204) having at least a BF acquisition mode, wherein the training method (100) uses as training data training Brightfield images (112, 112') and training fluorescent images (114, 114') of a fluorescently labelled training sample as ground truth which are automatically generated. It further relates to method for determining characterising parameters of a test ...

In general, the present invention relates to identification of lipidome biomarkers for cancer analysis and it provides prognostic and predictive methods and kits for cancer diagnosis and subtyping and for diagnosing and/or predicting the evolution of a tumor and its response to lipid metabolism-targeted or other types of therapy in a subject, by making use of phospholipid (PL) profiling, wherein changes in the combined acyl chain length of intact body fluid-derived or tumor-derived phospholipid species is indicative of an elongation phenotype.

Infliximab (IFX) is effective treatment for Crohn's disease (CD) and ulcerative colitis (UC) not responding to standard therapy. 30-40% of patients do not improve and response is often incomplete. The aim of this study is to identify mucosal gene signatures predictive of response to EFX using high-density oligonucleotide arrays. Eight UC patients and 12 CD patients showed healing. In UC, only one probe set was differentially expressed in responders compared with non-responders, ie IL-13Ralpha2. At PAM analysis 2 probe sets, representing IL-13Ralpha2 and IL-I l, separated IBD responders from ...