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1.
公开(公告)号:US20250014754A1
公开(公告)日:2025-01-09
申请号:US18635048
申请日:2024-04-15
Applicant: ZHEJIANG LAB
Inventor: Jingsong LI , Shengqiang CHI , Feng WANG , Tianshu ZHOU , Yu TIAN
IPC: G16H50/30 , G06F18/2413 , G16H50/20
Abstract: A clinical risk prediction system oriented to data distribution drift detection and self-adaptation, comprising a central server comprising a first drift detection module and a model aggregation module, and nodes comprising a data acquisition module configured to acquire patient clinical diagnosis and treatment data, a second drift detection module and a model updating module. The first and second drift detection module determine whether the patient clinical diagnosis and treatment data distribution has drifted according to whether the new/old patient clinical diagnosis and treatment data set comes from the same data distribution. When the data distribution has drifted, a local clinical risk prediction model is trained, and its parameters are uploaded to the central server and aggregated to obtain an updated model, which is issued to each node for deployment. The new patient clinical diagnosis and treatment data is input into the updated model to obtain a clinical risk prediction result.
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2.
公开(公告)号:US20240036860A1
公开(公告)日:2024-02-01
申请号:US18360840
申请日:2023-07-28
Applicant: ZHEJIANG LAB
Inventor: Jingsong LI , Hongyi NI , Tianshu ZHOU , Yu TIAN
Abstract: The present disclosure discloses a method and system for automatically and quickly deploying a front-end processor based on gray release. The system includes a user management module, a front-end processor engineering configuration module, a version iteration module and an engineering code version management repository, where the version iteration module is connected with the engineering code version management repository, the user management module and the front-end processor engineering configuration module, a code is obtained through the engineering code version management repository to perform updating or rollback of a current code, an operating permission of the front-end processor is obtained by using the user management module, an engineering configuration parameter is obtained from the front-end processor engineering configuration module for engineering gray release of a plurality of front-end processors, and a task scheduling function therein is called.
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3.
公开(公告)号:US20240021312A1
公开(公告)日:2024-01-18
申请号:US18352216
申请日:2023-07-13
Applicant: ZHEJIANG LAB
Inventor: Jingsong LI , Feng WANG , Shengqiang CHI , Yu TIAN , Tianshu ZHOU
Abstract: Disclosed is an system for predicting end-stage renal disease complication risk based on contrastive learning, including an end-stage renal disease data preparation module, configured to extract structured data of a patient by using a hospital electronic information system and daily monitoring equipment, and process the structured data to obtain augmented structured data; and a complication risk prediction module, configured to construct a complication representation learning model and a complication risk prediction model, perform training and learning on the augmented structured data through the complication representation learning model to obtain a complication representation, and perform end-stage renal disease complication risk prediction by using the complication representation through the complication risk prediction model.
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4.
公开(公告)号:US20240079022A1
公开(公告)日:2024-03-07
申请号:US18360838
申请日:2023-07-28
Applicant: ZHEJIANG LAB
Inventor: Jingsong LI , Zhenchuan ZHANG , Tianshu ZHOU , Yu TIAN
IPC: G10L21/0232 , G10L17/02 , G10L17/04 , G10L25/30
CPC classification number: G10L21/0232 , G10L17/02 , G10L17/04 , G10L25/30
Abstract: The present disclosure discloses a general speech enhancement method and apparatus using multi-source auxiliary information. The method includes following steps: S1: building a training data set; S2: using the training data set to learn network parameters of a model, and building a speech enhancement model; S3: building a sound source information database in a pre-collection or on-site collection mode; S4: acquiring an input of the speech enhancement model; and S5: taking a noisy original signal as a main input of the speech enhancement model, taking auxiliary sound signals of a target source group and auxiliary sound signals of an interference source group as side inputs of the speech enhancement model for speech enhancement, and obtaining an enhanced speech signal.
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公开(公告)号:US20240013000A1
公开(公告)日:2024-01-11
申请号:US18348317
申请日:2023-07-06
Applicant: ZHEJIANG LAB
Inventor: Jingsong LI , Lixin SHI , Ran XIN , Zongfeng YANG , Yu TIAN , Tianshu ZHOU
IPC: G06F40/295 , G06F40/169 , G06F40/30 , G06F40/40 , G06F40/284
CPC classification number: G06F40/295 , G06F40/169 , G06F40/30 , G06F40/40 , G06F40/284
Abstract: Disclosed is a method and an apparatus NER-orientated Chinese clinical text data augmentation, and unannotated data and annotated data of label linearization processing through data preprocessing. A concealed part is predicted based on retained information by using the unannotated data and concealing part of information in text, and meanwhile an entity word-level discrimination task is introduced for pre-training of a span-based language model; and a plurality of decoding mechanisms are introduced in a fine-tune stage, a relationship between a text vector and text data is obtained based on the pre-trained span-based language model, linearized data with entity labels is converted into the text vector, and text generation is performed through forward decoding and reverse decoding in a prediction stage of a text generation model to obtain enhanced data with annotation information.
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6.
公开(公告)号:US20220157468A1
公开(公告)日:2022-05-19
申请号:US17553832
申请日:2021-12-17
Applicant: ZHEJIANG LAB
Inventor: Jingsong LI , Shiqiang ZHU , Tianshu ZHOU , Yu TIAN
Abstract: Provided is a patient data visualization method and system for assisting decision making in chronic diseases. According to the present application, a management data model diagram of a patient on a hyperplane is constructed by constructing a chronic disease knowledge graph, and combining static data and dynamic data of the patient, and then the management data model diagram is projected onto a two-dimensional plane. The difference of the Euclidean distance between features of a patient information model on a two-dimensional plane graph from the distance of standard features is compared, and a management plan is generated and recommended in combination with path node concepts and an attribute relationship between the concepts.
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7.
公开(公告)号:US20240169610A1
公开(公告)日:2024-05-23
申请号:US18363703
申请日:2023-08-01
Applicant: ZHEJIANG LAB
Inventor: Jingsong LI , Yiwei GAO , Peijun HU , Tianshu ZHOU , Yu TIAN
CPC classification number: G06T11/006 , G06T3/4053 , G06T5/002 , G06T11/005 , G16H30/40 , G06T2207/10081 , G06T2207/20081 , G06T2207/20084 , G06T2207/30004 , G06T2207/30168 , G06T2211/441
Abstract: The present application discloses a label-free adaptive CT super-resolution reconstruction method, device and system based on a generative network, which comprises the following modules: an acquisition module configured for acquiring low-resolution original CT image data; a preprocessing module configured for performing super-resolution reconstruction on original CT images based on total variation to obtain an initial value; and a super-resolution reconstruction module configured for performing high-resolution reconstruction on the initial value. According to the present application, a parameter fine-tuning method is adopted, and a CT reconstruction network which is not suitable for a certain patient is adjusted into a network which is suitable for the patient's situation on the premise of not using a large number of data sets for training; only the low-resolution CT data of the patient is used in this process, and the corresponding high-resolution CT data is not needed as a label.
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8.
公开(公告)号:US20240168618A1
公开(公告)日:2024-05-23
申请号:US18363679
申请日:2023-08-01
Applicant: ZHEJIANG LAB
Inventor: Jingsong LI , Feixiang SONG , Bo ZHANG , Tianshu ZHOU , Yu TIAN
IPC: G06F3/04845 , G06F3/0354 , G06F3/0487 , G06T3/40 , G06T5/00 , G06T7/11 , G16H30/20
CPC classification number: G06F3/04845 , G06F3/03543 , G06F3/0487 , G06T3/40 , G06T5/002 , G06T7/11 , G16H30/20 , G06T2200/24 , G06T2207/20016 , G06T2207/20021 , G06T2207/20092 , G06T2207/30056
Abstract: The present application discloses a method and a system for displaying a high-resolution liver cancer pathological image based on an image pyramid, which comprises a data source processing module used for acquiring original images in various states, processing the original images, acquiring an image pyramid, naming image blocks in the image pyramid and storing the image blocks in a folder set for the image pyramid in a server; an image display module used for acquiring the image blocks in the folder set for the image pyramid in the server, acquiring the image blocks according to a user's request and splicing and displaying the image blocks in an image display area, wherein enlargement, reduction and translation operations are supported.
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9.
公开(公告)号:US20240054360A1
公开(公告)日:2024-02-15
申请号:US18358051
申请日:2023-07-25
Applicant: ZHEJIANG LAB
Inventor: Tianshu ZHOU , Yifan JIANG , Jingsong LI , Yu TIAN , Ying ZHANG
CPC classification number: G06N5/022 , G06T5/10 , G06T11/20 , G06V10/751 , G06V10/761 , G16H10/60 , G16H50/70 , G06T2207/20052
Abstract: The present disclosure discloses a similar patients identification method and system based on a patient representation image. The method includes following steps: S1: building a healthcare knowledge graph: generating the healthcare knowledge graph by extracting entities and a relationship between the entities in a knowledge source; S2: building a healthcare knowledge graph space vector library; S3: building a patient's personal healthcare knowledge graph space vector data set; S4: drawing a patient's personal healthcare representation image; and S5: performing similar patients identification based on graph similarity calculation. The present disclosure builds a visual patient representation mode, so as to convert patient's healthcare data into a visual image, so that a doctor may intuitively feel a difference of different patients and similarity of similar patients.
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10.
公开(公告)号:US20240038083A1
公开(公告)日:2024-02-01
申请号:US18360832
申请日:2023-07-28
Applicant: ZHEJIANG LAB
Inventor: Jingsong LI , Huiyao SUN , Tianshu ZHOU , Yu TIAN , Ying ZHANG
Abstract: The present disclosure discloses a publicity-education pushing method and system based on a multi-source information fusion. The method includes: step S1: constructing a patient publicity-education knowledge graph, and pushing the patient publicity-education knowledge graph to a patient through a publicity-education applet; step S2: fusing and correcting patient basic information, patient diagnosis-treatment information, patient eye movement information and a patient personality inventory to obtain patient multi-source information; step S3: constructing a compliance prediction model through a neural network by using the patient multi-source information and collected patient medication taking behavior data; and step S5: building a system rule base, and after searching for a corresponding disease and treatment in the patient publicity-education knowledge graph through information returned by the system rule base, pushing the disease and the treatment to the patient through the publicity-education applet.
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