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167 条记录 (耗时 0.038 秒)

    Generalizable and interpretable deep learning framework for predicting MSI from histopathology slide images
    101.
    发明授权
    Generalizable and interpretable deep learning framework for predicting MSI from histopathology slide images 有权

    公开(公告)号：US11741365B2

    公开(公告)日：2023-08-29

    申请号：US16412362

    申请日：2019-05-14

    申请人： TEMPUS LABS, INC.

    发明人： Aly Azeem Khan

    IPC分类号： G06N5/02 ,  G06N3/084 ,  G06N20/10

    CPC分类号： G06N3/084 ,  G06N5/02 ,  G06N20/10

    摘要： A generalizable and interpretable deep learning model for predicting microsatellite instability from histopathology slide images is provided. Microsatellite instability (MSI) is an important genomic phenotype that can direct clinical treatment decisions, especially in the context of cancer immunotherapies. A deep learning framework is provided to predict MSI from histopathology images, to improve the generalizability of the predictive model using adversarial training to new domains, such as on new data sources or tumor types, and to provide techniques to visually interpret the topological and morphological features that influence the MSI predictions.

    Evaluating effect of event on condition using propensity scoring
    102.
    发明授权
    Evaluating effect of event on condition using propensity scoring 有权

    公开(公告)号：US11715565B2

    公开(公告)日：2023-08-01

    申请号：US16679054

    申请日：2019-11-08

    申请人： Tempus Labs, Inc.

    发明人： Ashraf Hafez ,  Caroline Epstein

    IPC分类号： G16H50/30 ,  G06F3/01 ,  G16H50/70

    CPC分类号： G16H50/30 ,  G06F3/011 ,  G16H50/70

    摘要： Systems and methods are provided for implementing a tool for evaluating an effect on an event, such as a medication or treatment, on a subject's condition, using a propensity model that identifies matched treatment and control cohorts within a base population of subjects. A propensity value threshold, which can be obtained based on user input, can be used to adjust the selection of subjects for treatment and control cohorts. The tool allows analyzing features of the subjects in the treatment and control groups, and further allows for evaluation and comparison of survival objectives of subjects in the treatment and control groups.

    ECG-Based Cardiovascular Disease Detection Systems and Related Methods
    107.
    发明申请
    ECG-Based Cardiovascular Disease Detection Systems and Related Methods 有权

    公开(公告)号：US20220384044A1

    公开(公告)日：2022-12-01

    申请号：US17829351

    申请日：2022-05-31

    申请人： Tempus Labs, Inc. ,  Geisinger Clinic

    发明人： Alvaro E. Ulloa-Cerna ,  Noah Zimmerman ,  Greg Lee ,  Christopher M. Haggerty ,  Brandon K. Fomwalt ,  Ruijun Chen ,  John Pfeifer ,  Chris Good

    IPC分类号： G16H50/30 ,  A61B5/00 ,  A61B5/28

    摘要： A method for determining cardiology disease risk from electrocardiogram trace data and clinical data includes receiving electrocardiogram trace data associated with a patient, receiving the patient's clinical data, providing both sets of data to a trained machine learning composite model that is trained to evaluate the data with respect to each disease of a set of cardiology diseases including three or more of cardiac amyloidosis, aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid regurgitation, abnormal reduced ejection fraction, or abnormal interventricular septal thickness, generating, by the model and based on the evaluation, a composite risk score reflecting a likelihood of the patient being diagnosed with one or more of the cardiology diseases within a predetermined period of time from when the electrocardiogram trace data was generated, and outputting the composite risk score to at least one of a memory or a display.

    MOLECULAR RESPONSE AND PROGRESSION DETECTION FROM CIRCULATING CELL FREE DNA
    108.
    发明申请
    MOLECULAR RESPONSE AND PROGRESSION DETECTION FROM CIRCULATING CELL FREE DNA 有权

    公开(公告)号：US20220367010A1

    公开(公告)日：2022-11-17

    申请号：US17859599

    申请日：2022-07-07

    申请人： Tempus Labs, Inc.

    发明人： Justin David Finkle ,  Christine Lo ,  Jonathan Alexander Heiss ,  Robert Tell ,  Sun Hae Hong

    IPC分类号： G16B40/00 ,  G16B20/20 ,  G16B5/20 ,  G06F30/27

    摘要： Methods, systems, and software are provided for monitoring a cancer condition of a test subject. The method includes obtaining a liquid biopsy sample from the subject at a second time point, occurring after a first time point, containing cell-free DNA fragments. Low-pass whole genome methylation sequencing of the cell-free DNA fragments is performed to obtain nucleic acid sequences having a methylation pattern for a corresponding cell-free DNA fragment. The nucleic acid sequences are mapped to a location on a reference genome. Methylation metrics are determined based on the methylation patterns and mapped locations of the nucleic acid sequences. A circulating tumor fraction is estimated from the methylation metrics, and the estimate is compared to an estimate of the circulating tumor fraction for the test subject at the first time point.

    Systems and Methods for Interrogating Clinical Documents for Characteristic Data
    109.
    发明申请
    Systems and Methods for Interrogating Clinical Documents for Characteristic Data 有权

    公开(公告)号：US20220319652A1

    公开(公告)日：2022-10-06

    申请号：US17837025

    申请日：2022-06-10

    申请人： Tempus Labs, Inc.

    发明人： Jonathan Ozeran

    IPC分类号： G16H10/60 ,  G16H50/20 ,  G06Q50/22 ,  G06F40/186

    摘要： A computer program product includes multiple microservices for interrogating clinical records according to one or more projects associated with patient datasets obtained from electronic copies of source documents from the clinical records. A first microservice generates a user interface including a first portion displaying source documents and, concurrently, a second portion displaying structured patient data fields organized into categories for entering structured patient data derived from the source documents displayed in the first portion. Categories and their organization are defined by a template and include cancer diagnosis, staging, tumor size, genetic results, and date of recurrence. A second microservice validates abstracted patient data according to validation rules applied to the categories, validation rules being assigned to the projects and performed on the categories as they are populated. A third microservice provides abstraction review performed by an assigned abstractor or an abstraction manager and spans one or more of the projects.

    ARTIFICIAL INTELLIGENCE ENGINE FOR DIRECTED HYPOTHESIS GENERATION AND RANKING
    110.
    发明申请
    ARTIFICIAL INTELLIGENCE ENGINE FOR DIRECTED HYPOTHESIS GENERATION AND RANKING 有权

    公开(公告)号：US20220261668A1

    公开(公告)日：2022-08-18

    申请号：US17651002

    申请日：2022-02-14

    申请人： Tempus Labs, Inc.

    发明人： Martin Stumpe ,  Alena Harley

    IPC分类号： G06N5/04 ,  G06F16/28 ,  G06F16/2457

    摘要： An artificial intelligence engine for directed hypothesis generation and ranking uses multiple heterogeneous knowledge graphs integrating disease-specific multi-omic data specific to a patient or cohort of patients. The engine also uses a knowledge graph representation of ‘what the world knows’ in the relevant bio-medical subspace. The engine applies a hypothesis generation module, a semantic search analysis component to allow fast acquiring and construction of cohorts, as well as aggregating, summarizing, visualizing and returning ranked multi-omic alterations in terms of clinical actionability and degree of surprise for individual samples and cohorts. The engine also applies a moderator module that ranks and filters hypotheses, where the most promising hypothesis can be presented to domain experts (e.g., physicians, oncologists, pathologists, radiologists and researchers) for feedback. The engine also uses a continuous integration module that iteratively refines and updates entities and relationships and their representations to yield higher quality of hypothesis generation over time.