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    Machine learning augmented system for medical episode identification and reporting
    32.
    发明授权
    Machine learning augmented system for medical episode identification and reporting 有权

    公开(公告)号：US12020816B2

    公开(公告)日：2024-06-25

    申请号：US17483895

    申请日：2021-09-24

    申请人： Merative US L.P.

    发明人： Raman Srinivasan ,  Ajay Ashok Deshpande

    IPC分类号： G16H50/20 ,  G06F16/28 ,  G16H10/60

    CPC分类号： G16H50/20 ,  G06F16/283 ,  G16H10/60

    摘要： A medical episode analysis engine is provided. The engine generates a first matrix data structure having an entry for each concept pairing and storing a value representing relatedness weighted according to a temporal weighting function. The engine generates a second matrix data structure by calculating, for each entry in the first matrix, a relatedness measure of the concepts in the concept pairing based on a frequency of occurrence together. The engine generates, for each first concept, a concept embedding, based on the second matrix, that specifies, for each other second concept, a temporally weighted relatedness measure. The engine generates, for each anchor concepts, a corresponding episode definition comprising a plurality of related concepts corresponding to a same episode, based on the concept embedding. The engine processes new input data based on the episode definition data structures to identify instances of corresponding episodes in the new input data.

    Deduplication of Medical Concepts from Patient Information
    35.
    发明公开
    Deduplication of Medical Concepts from Patient Information 审中-公开

    公开(公告)号：US20230360751A1

    公开(公告)日：2023-11-09

    申请号：US18221597

    申请日：2023-07-13

    申请人： Merative US L.P.

    发明人： Tanveer F. Syeda-Mahmood ,  Chaitanya Shivade

    IPC分类号： G16H10/60 ,  G16H50/70 ,  G16H70/60 ,  G16H15/00

    CPC分类号： G16H10/60 ,  G16H50/70 ,  G16H70/60 ,  G16H15/00

    摘要： Mechanisms are provided to implement a patient summary generation engine with deduplication of instances of medical concepts. The patient summary generation engine parses a patient electronic medical record (EMR) to extract a plurality of instances of a medical concept, at least two of which utilize different representations of the medical concept. The patient summary generation engine performs a similarity analysis between each of the instances of a medical concept to thereby calculate, for a plurality of combinations of instances of the medical concept, a similarity metric value. The patient summary generation engine clusters the instances of the medical concept based on the calculated similarity metric values for each combination of instances in the plurality of combinations of instances of the medical concept to thereby generate one or more clusters, and select a representative instance of the medical concept from each cluster in the one or more clusters. The patient summary generation engine generates a summary output of the patient EMR comprising the selected representative instances of the medical concept from each cluster.

    Deduplication of medical concepts from patient information
    38.
    发明授权
    Deduplication of medical concepts from patient information 有权

    公开(公告)号：US11749387B2

    公开(公告)日：2023-09-05

    申请号：US17350441

    申请日：2021-06-17

    申请人： Merative US L.P.

    发明人： Tanveer F. Syeda-Mahmood ,  Chaitanya Shivade

    IPC分类号： G16H10/60 ,  G16H50/70 ,  G16H70/60 ,  G16H15/00

    CPC分类号： G16H10/60 ,  G16H15/00 ,  G16H50/70 ,  G16H70/60

    摘要： Mechanisms are provided to implement a patient summary generation engine with deduplication of instances of medical concepts. The patient summary generation engine parses a patient electronic medical record (EMR) to extract a plurality of instances of a medical concept, at least two of which utilize different representations of the medical concept. The patient summary generation engine performs a similarity analysis between each of the instances of a medical concept to thereby calculate, for a plurality of combinations of instances of the medical concept, a similarity metric value. The patient summary generation engine clusters the instances of the medical concept based on the calculated similarity metric values for each combination of instances in the plurality of combinations of instances of the medical concept to thereby generate one or more clusters, and select a representative instance of the medical concept from each cluster in the one or more clusters. The patient summary generation engine generates a summary output of the patient EMR comprising the selected representative instances of the medical concept from each cluster.

    Determining drug effectiveness ranking for a patient using machine learning
    40.
    发明授权
    Determining drug effectiveness ranking for a patient using machine learning 有权

    公开(公告)号：US11721441B2

    公开(公告)日：2023-08-08

    申请号：US16248084

    申请日：2019-01-15

    申请人： Merative US L.P.

    发明人： Cheryl L. Eifert ,  Jia Xu ,  Claudia S Huettner ,  Fang Wang ,  Vanessa Michelini ,  Elinor Dehan

    IPC分类号： G16H70/40 ,  G16B50/00 ,  G16B40/00 ,  G16H70/60

    CPC分类号： G16H70/40 ,  G16B40/00 ,  G16B50/00 ,  G16H70/60

    摘要： Computer based methods, systems, and computer readable media for intelligently accessing various types of pharmaceutical information in a content repository and ranking drugs at the variant level, gene level, and pathway level. In some cases, drugs that target the same gene, gene variant, or biological pathway may be ranked based upon in vitro, pre-clinical, clinical, or post-clinical evidence. To determine ranking of a plurality of drugs, information pertaining to drug administration is analyzed for the drugs. For a plurality of drugs, attributes corresponding to the drug are determined, wherein the attributes include a variant or a gene targeted by the drug, and a biological pathway comprising the targeted variant or gene. The plurality of drugs are ranked according to a drug effectiveness score based on one or more of a determined efficacy, potency, or toxicity.