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    Condensed memory networks
    3.
    发明授权
    Condensed memory networks 有权

    公开(公告)号：US11620506B2

    公开(公告)日：2023-04-04

    申请号：US15707550

    申请日：2017-09-18

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Aaditya Prakash ,  Sheikh Sadid AL Hasan ,  Oladimeji Feyisetan Farri ,  Kathy Mi Young Lee ,  Vivek Varma Datla ,  Ashequl Qadir ,  Junyi Liu

    IPC: G06N3/08 ,  G06N3/04 ,  G16H50/20

    Abstract: Techniques are described herein for training and applying memory neural networks, such as “condensed” memory neural networks (“C-MemNN”) and/or “average” memory neural networks (“A-MemNN”). In various embodiments, the memory neural networks may be iteratively trained using training data in the form of free form clinical notes and clinical reference documents. In various embodiments, during each iteration of the training, a so-called “condensed” memory state may be generated and used as part of the next iteration. Once trained, a free form clinical note associated with a patient may be applied as input across the memory neural network to predict one or more diagnoses or outcomes of the patient.

    Patient-centric clinical knowledge discovery system
    4.
    发明授权
    Patient-centric clinical knowledge discovery system 有权

    公开(公告)号：US11544587B2

    公开(公告)日：2023-01-03

    申请号：US16340480

    申请日：2017-09-25

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Oladimeji Feyisetan Farri ,  Sheikh Al Hasan ,  Junyi Liu ,  Kathy Mi Young Lee ,  Vivek Varma Datla

    IPC: G16H50/20 ,  G06N5/04 ,  G06F16/35 ,  G16H50/70 ,  G16H15/00 ,  G06N3/08 ,  G06F40/30

    Abstract: A medical information retrieval system comprises a natural language processing system that processes a vocal user query to identify key words and phrases. These key words and phrases are provided to an inferencing engine that provides a set of knowledge-based inferences from medical knowledge sources, based on these key words and phrases. Thereafter, these knowledge-based inferences are provided to an information retrieval engine that retrieves a corresponding plurality of medical articles based on these knowledge-based inferences, and ranks each with respect to the knowledge-based inferences. A summary engine receives the ranked articles and creates a model based on the topical keywords and candidate sentences found in the highly ranked articles. A paraphrase engine processes the candidate sentences to provide a summary response based on a knowledge-based paraphrase model. An audio output device renders the summary report as the response to the user's original vocal query.

    PATIENT-CENTRIC CLINICAL KNOWLEDGE DISCOVERY SYSTEM
    7.
    发明申请
    PATIENT-CENTRIC CLINICAL KNOWLEDGE DISCOVERY SYSTEM 审中-公开

    公开(公告)号：US20190244119A1

    公开(公告)日：2019-08-08

    申请号：US16340480

    申请日：2017-09-25

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Oladimeji Feyisetan Farri ,  Sheikh Al Hasan ,  Junyi Liu ,  Kathy Mi Young Lee ,  Vivek Varma Datla

    IPC: G06N5/04 ,  G16H50/20 ,  G06N3/08

    CPC classification number: G06N5/04 ,  G06F16/35 ,  G06F17/2785 ,  G06N3/08 ,  G16H15/00 ,  G16H50/20 ,  G16H50/70

    Abstract: A medical information retrieval system comprises a natural language processing system that processes a vocal user query to identify key words and phrases. These key words and phrases are provided to an inferencing engine that provides a set of knowledge-based inferences from medical knowledge sources, based on these key words and phrases. Thereafter, these knowledge-based inferences are provided to an information retrieval engine that retrieves a corresponding plurality of medical articles based on these knowledge-based inferences, and ranks each with respect to the knowledge-based inferences. A summary engine receives the ranked articles and creates a model based on the topical keywords and candidate sentences found in the highly ranked articles. A paraphrase engine processes the candidate sentences to provide a summary response based on a knowledge-based paraphrase model. An audio output device renders the summary report as the response to the user's original vocal query.

    Systems, methods, and apparatus for diagnostic inferencing with a multimodal deep memory network
    10.
    发明授权
    Systems, methods, and apparatus for diagnostic inferencing with a multimodal deep memory network 有权

    公开(公告)号：US11621075B2

    公开(公告)日：2023-04-04

    申请号：US16330174

    申请日：2017-09-05

    Applicant: KONINKLIJKE PHILIPS N.V.

    Inventor： Sheikh Sadid Al Hasan ,  Siyuan Zhao ,  Oladimeji Feyisetan Farri ,  Kathy Mi Young Lee ,  Vivek Datla ,  Ashequl Qadir ,  Junyi Liu ,  Aaditya Prakash

    IPC: G16H50/20 ,  G16H15/00 ,  G06N3/04 ,  G06N3/049

    Abstract: The described embodiments relate to systems, methods, and apparatus for providing a multimodal deep memory network (200) capable of generating patient diagnoses (222). The multimodal deep memory network can employ different neural networks, such as a recurrent neural network and a convolution neural network, for creating embeddings (204, 214, 216) from medical images (212) and electronic health records (206). Connections between the input embeddings (204) and diagnoses embeddings (222) can be based on an amount of attention that was given to the images and electronic health records when creating a particular diagnosis. For instance, the amount of attention can be characterized by data (110) that is generated based on sensors that monitor eye movements of clinicians observing the medical images and electronic health records. Resulting patient diagnoses can be provided according to a predetermined classification of weights, or a compilation of words that are generated over multiple iterations of the multimodal deep memory network.

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