Detection of Human Leukocyte Antigen Loss of Heterozygosity

    公开(公告)号:US20210327536A1

    公开(公告)日:2021-10-21

    申请号:US17304940

    申请日:2021-06-28

    申请人: TEMPUS LABS, INC.

    IPC分类号: G16B20/10 G16B40/00 G16B30/10

    摘要: Processes are provided for detecting loss of heterozygosity of Human Leukocyte Antigen (HLA) in a subject using analysis of next generation sequencing (NGS) data. The processes include aligning NGS data and identifying unmapped and mapped reads, updating reference data, and feeding one or more sequence reads to an HLA typing process for identifying candidate HLA alleles and feeding HLA type data to a loss of heterozygosity (LOH) modeling process for determining a LOH status for each HLA allele. A report may be generated of the LOH statuses for each of HLA allele.

    MOBILE SUPPLEMENTATION, EXTRACTION, AND ANALYSIS OF HEALTH RECORDS

    公开(公告)号:US20210151192A1

    公开(公告)日:2021-05-20

    申请号:US17157974

    申请日:2021-01-25

    申请人: Tempus Labs, Inc.

    摘要: A system, method, and mobile device application are configured to capture, with a mobile device, a document such as a next generation sequencing (NGS) report that includes NGS medical information about a genetically sequenced patient. The method includes receiving, from a mobile device, an image of a medical document comprising NGS medical information of the patient, extracting a first region from the image, extracting NGS medical information of the patient from the first region into a structured dataset, the extracted NGS medical information including at least one RNA expression, correlating a portion of the extracted NGS medical information that includes the at least one RNA expression with summarized medical information from a cohort of patients similar to the patient, and generating, for display on the mobile device, a clinical decision support report comprising the summarized medical information.

    SYSTEMS AND METHODS FOR NEXT GENERATION SEQUENCING UNIFORM PROBE DESIGN

    公开(公告)号:US20210115511A1

    公开(公告)日:2021-04-22

    申请号:US17076704

    申请日:2020-10-21

    申请人: Tempus Labs, Inc.

    发明人: Richard Blidner

    IPC分类号: C12Q1/6874 C12Q1/6883

    摘要: Systems and methods are provided for determining an optimized probe set. The method proceeds by obtaining a set of probes, where each probe has a respective concentration. The set of probes is assayed against a sample library, and at least i) a respective recovery rate for each probe in the set of probes, and ii) a median recovery rate for the set of probes are obtained. Modify the respective concentration of each probe that does not satisfy predetermined recovery rate threshold. Reevaluate the set of probes against the sample library. Repeat the modifying and reevaluation until the respective updated recovery rate for each probe in the updated set of probes satisfies the predetermined recovery rate threshold, thereby providing the optimized set of probes for the sample library.

    Unsupervised Learning And Prediction Of Lines Of Therapy From High-Dimensional Longitudinal Medications Data

    公开(公告)号:US20210057071A1

    公开(公告)日:2021-02-25

    申请号:US17001673

    申请日:2020-08-24

    申请人: Tempus Labs, Inc.

    摘要: In one aspect, the present disclosure provides a method for labeling one or more medications concurrently administered to a patient as a line of therapy. The method includes identifying medical records of the patient from a plurality of digital records, creating, from the subset of medical records, a plurality of treatment intervals including at least one medication administered to the patient and a time interval, associating medications of the one or more treatments with a respective treatment interval when the administration of the medication falls within the time interval, refining the time interval of a respective treatment interval when a treatment of the one or more treatments falls outside the time interval but within an extension period, identifying one or more potential lines of therapy from the plurality of treatment intervals, and labeling the potential line of therapy having the highest maximum likelihood estimation as the line of therapy.

    ARTIFICIAL INTELLIGENCE SEGMENTATION OF TISSUE IMAGES

    公开(公告)号:US20200211189A1

    公开(公告)日:2020-07-02

    申请号:US16732242

    申请日:2019-12-31

    申请人: TEMPUS LABS, INC.

    IPC分类号: G06T7/00 G06T7/11

    摘要: Techniques for generating an overlay map on a digital medical image of a slide are provided, and include cell detection and tissue classification processes. Techniques include receiving a medical image, separating the image into tiles, and performing tile classifications and tissue classifications based on a multi-tile analysis. Techniques additionally include identifying cell objects in the image, separating the image into and displaying polygons identifying the cell objects and cell classifications. Generated displays may be overlays over the initial digital image.