中科微点-全球专利检索

  1. Login
  2. Sign Up

Search Results

514 records (took 0.027 seconds)

    Topical mTOR inhibitors for cutaneous proliferative and vascular conditions
    3.
    发明授权
    Topical mTOR inhibitors for cutaneous proliferative and vascular conditions 有权

    公开(公告)号：US12109199B2

    公开(公告)日：2024-10-08

    申请号：US16967457

    申请日：2019-02-06

    Applicant: Georgetown University

    Inventor： Cynthia Marie Carver Deklotz ,  Robert A. Silverman

    IPC: A61K31/436 ,  A61K9/00

    CPC classification number: A61K31/436 ,  A61K9/0014

    Abstract: Methods for the treatment of cutaneous vascular conditions and cutaneous proliferative conditions are provided. The methods employ topical administration of mammalian target of rapamycin (mTOR) inhibitors such as sirolimus (rapamycin) and everolimus. Conditions treatable by the disclosed methods include venolymphatic malformations, acne, acne rosacea, periorificial dermatitis, acne vulgaris, cutaneous capillary malformation-arteriovenous malformation (CM-AVM) syndrome, RASopathies, Langerhans cell histiocytosis, non-Langerhans cell histiocytosis, scars, hypertrophic or keloidal scars, Proteus syndrome, PIK3CA-related overgrowth spectrum (PROS), PTEN hamartoma tumor syndromes, cutaneous malignancies and tumors associated with PI3K/AKT/mTOR mutations, keratodermas, acanthosis nigricans, Birt-Hogg-Dube syndrome, Brooke-Speigler syndrome, cylindromas, and epidermal nevi. Also provided are formulations and pharmaceutical compositions having mTOR inhibitor as principal therapeutically active ingredient useful in practicing the methods.

    Method and system for assessing drug efficacy using multiple graph kernel fusion
    5.
    发明授权
    Method and system for assessing drug efficacy using multiple graph kernel fusion 有权

    公开(公告)号：US11869664B2

    公开(公告)日：2024-01-09

    申请号：US17852521

    申请日：2022-06-29

    Applicant: Georgetown University

    Inventor： Ophir Frieder ,  Hao-Ren Yao ,  Der-Chen Chang

    IPC: G06N7/01 ,  G16H50/20 ,  G16H20/10 ,  G16H70/40 ,  G06F9/54 ,  G16H50/80 ,  G06F18/24

    CPC classification number: G16H50/20 ,  G06F9/545 ,  G06F18/24 ,  G06N7/01 ,  G16H20/10 ,  G16H50/80 ,  G16H70/40

    Abstract: Embodiments of the present systems and methods may provide techniques to predict the success or failure of a drug used for disease treatment. For example, a method of determining drug efficacy may include, for a plurality of patients, generating a directed acyclic graph from health related information of each patient comprising nodes representing a medical event of the patient, at least one first edge connecting the first node to an additional node, each additional edge connecting nodes representing two consecutive medical events, the edge having a weight based on a time difference between the two consecutive medical events, capturing a plurality of features from each directed acyclic graph, generating a binary graph classification model on captured features of each directed acyclic graph, determining a probability that a drug or treatment will be effective using the binary graph classification model, and determining a drug to be prescribed to a patient based on the determined probability.

    ASSESSING DISEASES BY ANALYZING GAIT MEASUREMENTS
    6.
    发明公开
    ASSESSING DISEASES BY ANALYZING GAIT MEASUREMENTS 审中-公开

    公开(公告)号：US20230355136A1

    公开(公告)日：2023-11-09

    申请号：US18159847

    申请日：2023-01-26

    Applicant: Georgetown University

    Inventor： Gholam Motamedi ,  Ophir Frieder ,  Cristopher Flagg ,  Jian-Young Wu

    IPC: A61B5/11 ,  A61B5/00 ,  G06F40/205

    CPC classification number: A61B5/112 ,  A61B5/7267 ,  A61B5/742 ,  A61B5/7275 ,  G06F40/205 ,  A61B5/4842 ,  A61B2562/0247 ,  A61B2562/0219

    Abstract: A gait analysis system, which includes a neural network with a recurrent neural network layer and a fully connected layer, that receives sensor data indicative of an individual's gait and outputs an assessment regarding the individual's health. The neural network is trained using training data indicative of abnormal gaits and normal gaits. To analyze the training data and the sensor data, the recurrent neural network layer parses each piece of data into a series of windows and analyzes each window in series to generate a context vector characterizing each window and the previously analyzed windows. The fully connected layer, having been trained to differentiate between normal gaits and abnormal gaits based on context vectors characterizing the training data, is used to generate a final assessment characterizing the user gate as normal or abnormal using one or more of the context vectors characterizing the sensor data.

    Detecting infection using surrogates
    8.
    发明授权
    Detecting infection using surrogates 有权

    公开(公告)号：US11728042B2

    公开(公告)日：2023-08-15

    申请号：US17406598

    申请日：2021-08-19

    Applicant: Georgetown University

    Inventor： Howard Federoff ,  Ophir Frieder

    IPC: G16H50/80 ,  G16H50/30 ,  G16H40/67 ,  G10L25/66

    CPC classification number: G16H50/80 ,  G10L25/66 ,  G16H40/67 ,  G16H50/30

    Abstract: A triage system that determines whether a user is likely to have contracted a disease based on sensor data received from a user device (e.g., a smartphone or activity tracker). Each symptom is identified by comparing sensor data to a predetermined baseline and comparing the difference to a predetermined symptom threshold. Because direct measurement of symptoms using the sensors available to the user may not be feasible or sufficiently accurate, the triage system also uses surrogates the identify certain symptoms. For example, a fever may be identified using heart data, a cough or shortness of breath may be identified by analyzing recorded sound, fatigue may be identified by analyzing the movement of the user device, and loss of smell or taste may be identified by recording sound and using speech detection algorithms to identify phrases in the recorded sound indicative of loss of smell or taste.

Patent Agency Ranking