Abstract:
The present invention relates to a method of adapting a composite signature of a phenotype. The method comprises the steps of providing for a composite signature of a phenotype with at least two different data types, which were respectively generated by two different modalities of measuring a specimen. Due to an adaption of one part of the signature of the phenotype the resulting adapted phenotype signature can be used as an input for a signature evaluation tool that was derived from data measured by a third modality of measurement.
Abstract:
Provided is a method for the analysis of breast cancer disorders, comprising determining the genomic methylation status of one or more CpG dinucleotides. Furthermore, a computer program product stored on a computer-readable medium comprising software code adapted to perform the steps of the method when executed on a data-processing apparatus is provided. A device comprising means for supporting a clinician is also provided.
Abstract:
The present invention relates to effective diagnosis of patients and assisting clinicians in treatment planning. In particular, invention provides a medical analysis system that enables refinement of molecular classification. The system provides a molecular profiling solution that will allow improved diagnosis, prognosis, response prediction to provide the right chemotherapy, and follow-up to monitor for cancer recurrence.
Abstract:
A method for providing personalized news to a consumer is provided that includes receiving news from a plurality of external sources. A subset of the received news is identified based on a consumer profile for the consumer. The identified news is stored. The stored news is prioritized. At least a portion of the prioritized news is provided to the consumer.
Abstract:
The present invention relates to a method for stratifying a patient into a clinically relevant group comprising the identification of the probability of an alteration within one or more sets of molecular data from a patient sample in comparison to a database of molecular data of known phenotypes, the inference of the activity of a biological network on the basis of the probabilities, the identification of a network information flow probability for the patient via the probability of interactions in the network, the creation of multiple instances of network information flow for the patient sample and the calculation of the distance of the patient from other subjects in a patient database using multiple instances of the network information flow. The invention further relates to a biomedical marker or group of biomedical markers associated with a high likelihood of responsiveness of a subject to a cancer therapy wherein the biomedical marker or group of biomedical markers comprises altered biological pathway markers, as well as to an assay for detecting, diagnosing, graduating, monitoring or prognosticating a medical condition, or for detecting, diagnosing, monitoring or prognosticating the responsiveness of a subject to a therapy against said medical condition, in particular ovarian cancer. Furthermore, a corresponding clinical decision support system is provided.
Abstract:
A state machine (22) stores a current state (30) comprising a clinical context defined by available patient-related information relating to a medical patient, and identifies one or more available analytical tools of a set of analytical tools (24) that are applicable to the current state. A graphical user interface module (16) receives a user selection of an available analytical tool. The state machine loads patient-related information (40) to the user-selected available analytical tool (24 sel ) and invokes the user-selected available analytical tool to operate on the loaded patient-related information to generate additional patient-related information relating to the medical patient and/or graphical patient-related content relating to the medical patient. The state machine transitions from the current state (30) to a next state (30') and/or invokes the graphical user interface module to display the graphical patient related content.
Abstract:
The present invention relates to a method for identifying multi-modal associations between biomedical markers which allows for the determination of network nodes and/or high ranking network members or combinations thereof, indicative of having a diagnostic, prognostic or predictive value for a medical condition, in particular ovarian cancer. The present invention further relates to a biomedical marker or group of biomedical markers associated with a high likelihood of responsiveness of a subject to a cancer therapy, preferably a platinum based cancer therapy, wherein said biomedical marker or group of biomedical markers comprises at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 8, 19, 20 or all markers selected from PKMYT1, SKIL, RAB8A, HIRIP3, CTNNB1, NGFR, ZCCHC11, LSP1, CD200, PAX8, CYBRD1, HOXC11, TCEAL1, FZD10,FZD1, BBS4, IRS2, TLX3, TSPAN2, TXN, and CFLAR. Furthermore, an assay for detecting, diagnosing, graduating, monitoring or prognosticating a medical condition, or for detecting, 1 diagnosing, monitoring or prognosticating the responsiveness of a subject to a therapy against said medical condition, in particular ovarian cancer, is provided, as well as a corresponding method for classifying a subject comprising and a medical decision support system.
Abstract:
Provided is a method for the analysis of breast cancer disorders, comprising determining the genomic methylation status of one or more CpG dinucleotides. Furthermore, a computer program product stored on a computer-readable medium comprising software code adapted to perform the steps of the method when executed on a data-processing apparatus is provided. A device comprising means for supporting a clinician is also provided.
Abstract:
A state machine (22) stores a current state (30) comprising a clinical context defined by available patient-related information relating to a medical patient, and identifies one or more available analytical tools of a set of analytical tools (24) that are applicable to the current state. A graphical user interface module (16) receives a user selection of an available analytical tool. The state machine loads patient-related information (40) to the user-selected available analytical tool (24sel) and invokes the user-selected available analytical tool to operate on the loaded patient-related information to generate additional patient-related information relating to the medical patient and/or graphical patient-related content relating to the medical patient. The state machine transitions from the current state (30) to a next state (30') and/or invokes the graphical user interface module to display the graphical patient related content.