Patents by Inventor Angel Janevski

Angel Janevski has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20200395128
    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.
    Type: Application
    Filed: June 2, 2020
    Publication date: December 17, 2020
    Inventors: Angel Janevski, Nevenka Dimitrova, Sitharthan Kamalakaran, Yasser Alsafadi, Nilanjana Banerjee, Anca Ioana Daniela Bucur, Jasper Johannes Adrianus van Leeuwen, Vinay Varadan
  • Patent number: 10679726
    Abstract: Relevance of a study genetic variant observed in diagnostic subject genetic data that is associated by a clinical study with a phenotype characteristic is assessed as follows. A set of polymorphisms functionally related to the study genetic variant are identified. A foreground distribution is computed of variants observed in the diagnostic subject genetic data for the set of polymorphisms. A background distribution is computed of variants observed in genetic data of subjects of the clinical study for the set of polymorphisms. A comparison metric is computed comparing the foreground distribution and the background distribution. Relevance of the study variant to the diagnostic subject is quantified based on the comparison metric, with higher similarity of the foreground and background distributions corresponding to higher relevance.
    Type: Grant
    Filed: November 15, 2013
    Date of Patent: June 9, 2020
    Assignee: Koninklijke Philips N.V.
    Inventors: Sitharthan Kalalakaran, Vinay Varadan, Nilanjana Banerjee, Angel Janevski, Nevenka Dimitrova
  • Patent number: 10541052
    Abstract: A catalog (34) of molecular marker tests specifies molecular marker tests annotated with clinical applicability annotations. An electronic patient medical record (22) stores genetic sequencing data (20) of a patient. A clinical decision support (CDS) system (30) is configured to track the clinical context of the patient wherein the clinical context includes at least a disease diagnosis and a current patient care stage. A catalog search module (32) is configured to search the catalog of molecular marker tests to identify a molecular marker test having clinical applicability to the patient in the clinical context tracked by the CDS system. The search is automatically triggered by occurrence of a trigger event defined by a set of triggering rules. A testing module (44) is configured to perform a molecular marker test identified by the identification module in silico using the genetic sequencing data of the patient stored in the electronic patient medical record.
    Type: Grant
    Filed: November 29, 2012
    Date of Patent: January 21, 2020
    Assignee: Koninklijke Philip N.V.
    Inventors: Vinay Varadan, Sitharthan Kamalakaran, Angel Janevski, Nilanjana Banerjee, Nevenka Dimitrova
  • Patent number: 10460831
    Abstract: In a predictive outcome assessment test for predicting whether a patient undergoing a breast cancer treatment regimen will achieve pathological complete response (pCR), differential gene expression level information are generated for an input set of genes belonging to the TGF-? signaling pathway. The differential gene expression level information compares baseline gene expression level information from a baseline sample (70) of a breast tumor of a patient acquired before initiating (71) a breast cancer therapy regimen to the patient and response gene expression level information from a response sample (72) of the breast tumor acquired after initiating the breast cancer therapy regimen by administering a first dose of bevacizumab to the patient. A pCR prediction for the patient is computed based on the differential gene expression level information for the input set of genes belonging to the TGF-? signaling pathway. Related predictive outcome assessment test development methods are also disclosed.
    Type: Grant
    Filed: November 22, 2013
    Date of Patent: October 29, 2019
    Assignee: Koninklijke Philips N.V.
    Inventors: Vinay Varadan, Sitharthan Kamalakaran, Angel Janevski, Nilanjana Banerjee, Nevenka Dimitrova, Lyndsay Harris
  • Patent number: 10340027
    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.
    Type: Grant
    Filed: October 4, 2011
    Date of Patent: July 2, 2019
    Assignee: Koninklijke Philips N.V.
    Inventors: Nilanjana Banerjee, Angel Janevski, Sitharthan Kamalakaran, Vinay Varadan, Nevenka Dimitrova, Robert Lucito
  • Publication number: 20180089392
    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.
    Type: Application
    Filed: November 29, 2017
    Publication date: March 29, 2018
    Inventors: Angel Janevski, Nevenka Dimitrova, Sitharthan Kamalakaran, Yasser Alsafadi, Nilanjana Banerjee, Anca Ioana Daniela Bacur, Jasper Johannes Adrianus van Leeuwen, Vinay Varadan
  • Patent number: 9798856
    Abstract: An imaging visualization workstation (30) includes a graphical display device (32) and an electronic data processor, and is configured to perform a method including: spatially registering a biopsy sample extracted from a medical subject with a medical image (12) of the medical subject; combining the medical image with a graphical representation of information (20, 22) generated from the biopsy sample to generate a combined image in which the graphical representation is spatially delineated based on the spatial registration of the biopsy sample; and displaying the combined image on the graphical display device of the imaging visualization workstation. A method comprises extracting a biopsy sample spatial sample from a medical subject, processing the biopsy sample to generate biopsy information, acquiring a medical image of the subject, spatially registering the biopsy sample with the medical image, and displaying the medical image modified to include an annotation generated from the biopsy information.
    Type: Grant
    Filed: March 20, 2013
    Date of Patent: October 24, 2017
    Assignee: Koninklijke Philips N.V.
    Inventors: Nilanjana Banerjee, Sitharthan Kamalakaran, Vinay Varadan, Angel Janevski, Nevenka Dimitrova
  • Publication number: 20170220773
    Abstract: An improved system for tracking the progress of a clinical study includes a classifier generator, a classifier application subsystem, a study stage annotation subsystem, a progress status models generator, an aggregation module, and a progress status evaluation subsystem.
    Type: Application
    Filed: February 3, 2016
    Publication date: August 3, 2017
    Inventors: Angel Janevski, Mladen Laudanovic
  • Patent number: 9552649
    Abstract: Image texture feature values are computed for a set of image texture features from an image of an anatomical feature of interest in a subject, and the subject is classified respective to a molecular feature of interest based on the computed image texture feature values. The image texture feature values may be computed from one or more gray level co-occurrence matrices (GLCMs), and the image texture features may include Haralick and/or Tamura image texture features. To train the classifier, reference image texture feature values are computed for at least the set of image texture features from images of the anatomical feature of interest in reference subjects. The reference image texture feature values are divided into different population groups representing different values of the molecular feature of interest, and the classifier is trained to distinguish between the different population groups based on the reference image texture feature values.
    Type: Grant
    Filed: October 25, 2013
    Date of Patent: January 24, 2017
    Assignee: Koninklijke Philips N.V.
    Inventors: Nilanjana Banerjee, Nevenka Dimitrova, Vinay Varadan, Sitharthan Kamalakaran, Angel Janevski, Sayan Maity
  • Publication number: 20160085943
    Abstract: A method for monitoring clinical trial progress includes calculating progress curves for clinical trial states. Calculating a progress curve includes assigning values to events for a datapoint in the clinical trial, generating or building pairs of values for each consecutive sequence of the events, summing up the values of pairs of events corresponding to a state change, and determining a state for the datapoint based on the sum of the values. Monitoring clinical trial progress then includes calculating a second progress curve for another clinical trial state and comparing the delay between points of the progress curves. A system for monitoring clinical trial progress is also described.
    Type: Application
    Filed: September 22, 2014
    Publication date: March 24, 2016
    Inventors: Glen de Vries, Mladen Laudanovic, Angel Janevski
  • Publication number: 20160012183
    Abstract: A medical system (50, 100) comprises at least one processor (32, 62, 120) programmed to receive patient-specific data of a patient. The patient-specific data includes at least one of: 1) image and/or map data; and 2) physiological data. The at least one processor (32, 62, 120) is further programmed to visually display at least some of the patient-specific data to a user of the medical system (50, 100) on a monitor (70, 128), and modulate a signal to convey data to the user using a sense other than sight. The signal is modulated based on at least one of: a parameter extracted from the patient-specific data; and a position of: 1) a displayed slice of an image and/or map of the patient-specific data; or 2) a device within the patient.
    Type: Application
    Filed: March 18, 2014
    Publication date: January 14, 2016
    Inventors: Angel Janevski, Lyubomir Georgiev Zagorchev
  • Publication number: 20150347679
    Abstract: In a predictive outcome assessment test for predicting whether a patient undergoing a breast cancer treatment regimen will achieve pathological complete response (pCR), differential gene expression level information are generated for an input set of genes belonging to the TGF-? signaling pathway. The differential gene expression level information compares baseline gene expression level information from a baseline sample (70) of a breast tumor of a patient acquired before initiating (71) a breast cancer therapy regimen to the patient and response gene expression level information from a response sample (72) of the breast tumor acquired after initiating the breast cancer therapy regimen by administering a first dose of bevacizumab to the patient. A pCR prediction for the patient is computed based on the differential gene expression level information for the input set of genes belonging to the TGF-? signaling pathway. Related predictive outcome assessment test development methods are also disclosed.
    Type: Application
    Filed: November 22, 2013
    Publication date: December 3, 2015
    Inventors: VINAY VARADAN, SITHARTHAN KAMALAKARAN, ANGEL JANEVSKI, NILANJANA BANERJEE, NEVENKA DIMITROVA, LYNDSAY HARRIS
  • Publication number: 20150310632
    Abstract: Image texture feature values are computed for a set of image texture features from an image of an anatomical feature of interest in a subject, and the subject is classified respective to a molecular feature of interest based on the computed image texture feature values. The image texture feature values may be computed from one or more gray level co-occurrence matrices (GLCMs), and the image texture features may include Haralick and/or Tamura image texture features. To train the classifier, reference image texture feature values are computed for at least the set of image texture features from images of the anatomical feature of interest in reference subjects. The reference image texture feature values are divided into different population groups representing different values of the molecular feature of interest, and the classifier is trained to distinguish between the different population groups based on the reference image texture feature values.
    Type: Application
    Filed: October 25, 2013
    Publication date: October 29, 2015
    Inventors: NILANJANA BANERJEE, NEVENKA DIMITROVA, VINAY VARADAN, SITHARTHAN KAMALAKARAN, ANGEL JANEVSKI, SAYAN MAITY
  • Publication number: 20150294063
    Abstract: Relevance of a study genetic variant observed in diagnostic subject genetic data that is associated by a clinical study with a phenotype characteristic is assessed as follows. A set of polymorphisms functionally related to the study genetic variant are identified. A foreground distribution is computed of variants observed in the diagnostic subject genetic data for the set of polymorphisms. A background distribution is computed of variants observed in genetic data of subjects of the clinical study for the set of polymorphisms. A comparison metric is computed comparing the foreground distribution and the background distribution. Relevance of the study variant to the diagnostic subject is quantified based on the comparison metric, with higher similarity of the foreground and background distributions corresponding to higher relevance.
    Type: Application
    Filed: November 15, 2013
    Publication date: October 15, 2015
    Applicant: KONINKLIJKE PHILIPS N.V.
    Inventors: Sitharthan Kalalakaran, Vinay Varadan, Nilanjana Banerjee, Angel Janevski, Nevenka Dimitrova
  • Patent number: 9074206
    Abstract: The present invention relates compositions and methods for microRNA (miRNA) expression profiling of colorectal cancer. In particular, the invention relates to a diagnostic kit of molecular markers for identifying one or more mammalian target cells exhibiting or having a predisposition to develop colorectal cancer, the kit comprising a plurality of nucleic acid molecules, each nucleic acid molecule encoding a miRNA sequence, wherein one or more of the plurality of nucleic acid molecules are differentially expressed in the target cells and in one or more control cells, and wherein the one or more differentially expressed nucleic acid molecules together represent a nucleic acid expression signature that is indicative for the presence of or the predisposition to develop colorectal cancer.
    Type: Grant
    Filed: November 13, 2009
    Date of Patent: July 7, 2015
    Assignee: Fudan University
    Inventors: Ying Wu, Hongguang Zhu, Jian Li, Liang Xu, Wilhelmus F. J. Verhaegh, Yiping Ren, Angel Janevski, Vinay Varadan, Zhaoyong Li, Nevenka Dimitrova
  • Publication number: 20150097868
    Abstract: An imaging visualization workstation (30) includes a graphical display device (32) and an electronic data processor, and is configured to perform a method including: spatially registering a biopsy sample extracted from a medical subject with a medical image (12) of the medical subject; combining the medical image with a graphical representation of information (20, 22) generated from the biopsy sample to generate a combined image in which the graphical representation is spatially delineated based on the spatial registration of the biopsy sample; and displaying the combined image on the graphical display device of the imaging visualization workstation. A method comprises extracting a biopsy sample spatial sample from a medical subject, processing the biopsy sample to generate biopsy information, acquiring a medical image of the subject, spatially registering the biopsy sample with the medical image, and displaying the medical image modified to include an annotation generated from the biopsy information.
    Type: Application
    Filed: March 20, 2013
    Publication date: April 9, 2015
    Inventors: Nilanjana Banerjee, Sitharthan Kamalakaran, Vinay Varadan, Angel Janevski, Nevenka Dimitrova
  • Publication number: 20150058322
    Abstract: When generating visual representations of gene activity pathways for clinical decision support, a validated pathway database that stores a plurality of validated pathways is accessed, wherein each pathway describes at least one interaction between a plurality of genes. A processor (18) is configured to execute computer-executable instructions stored in a memory (16), the instructions comprising visually representing gene activity level (28) for at least one gene across a plurality of populations, retrieving a pathway (32) from the validated pathway database, wherein the pathway includes the at least one gene, and visually representing gene activity levels for all genes in the pathway.
    Type: Application
    Filed: March 27, 2013
    Publication date: February 26, 2015
    Applicant: KONINKLIJKE PHILIPS N.V.
    Inventors: Nevenka Dimitrova, Angel Janevski, Nilanjana Banerjee, Vinay Varadan, Sitharthan Kamalakaran
  • Publication number: 20140379379
    Abstract: In a clinical decision support method, outputs of computer-implemented analytical modules are computed for a patient. Information is displayed for the patient pertaining to a clinical question comprising outputs computed for the patient of analytical modules associated with the clinical question. The analytical modules may include modules configured to perform in silico genetic/genomic tests using genetic/genome sequencing (whole genome, whole exome, whole transcriptome, targeted gene panels, etc) or microarray data. A clinical question-module matrix (CQ-M matrix) may be generated for the patient associating clinical questions with analytical modules, and the method may further include populating the clinical questions with outputs computed for the patient of the analytical modules associated with the clinical questions by the CQ-M matrix.
    Type: Application
    Filed: June 24, 2014
    Publication date: December 25, 2014
    Inventors: ANGEL JANEVSKI, SITHARTHAN KAMALAKARAN, NILANJANA BANERJEE, VINAY VARADAN, NEVENKA DIMITROVA, MINE DANISMAN TASAR
  • Publication number: 20140365243
    Abstract: A catalog (34) of molecular marker tests specifies molecular marker tests annotated with clinical applicability annotations. An electronic patient medical record (22) stores genetic sequencing data (20) of a patient. A clinical decision support (CDS) system (30) is configured to track the clinical context of the patient wherein the clinical context includes at least a disease diagnosis and a current patient care stage. A catalog search module (32) is configured to search the catalog of molecular marker tests to identify a molecular marker test having clinical applicability to the patient in the clinical context tracked by the CDS system. The search is automatically triggered by occurrence of a trigger event defined by a set of triggering rules. A testing module (44) is configured to perform a molecular marker test identified by the identification module in silico using the genetic sequencing data of the patient stored in the electronic patient medical record.
    Type: Application
    Filed: November 29, 2012
    Publication date: December 11, 2014
    Inventors: Vinay Varadan, Sitharthan Kamalakaran, Angel Janevski, Nilanjana Banerjee, Nevenka Dimitrova
  • Patent number: 8762072
    Abstract: This invention relates to a method and an apparatus for determining a reliability indicator for at least one set of signatures obtained from clinical data collected from a group of samples. The signatures are obtained by detecting characteristics in the clinical data from the group of sample sand each of the signatures generate a first set of stratification values that stratify the group of samples. At least one additional and parallel stratification source to the signatures obtained from group of sample sis provided, the at least one additional and parallel stratification source to the signatures being independent from the signatures and generates a second set of stratification values. A comparison is done for each respective sample, where the first stratification values are compared with a true reference stratification values, and where the second stratification values are compared with the true reference stratification values.
    Type: Grant
    Filed: September 24, 2009
    Date of Patent: June 24, 2014
    Assignee: Koninklijke Philips N.V.
    Inventors: Angel Janevski, Nilanjana Banerjee, Yasser Alsafadi, Vinay Varadan