-
11.发明公开公开(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.
-
12.发明申请公开(公告)号：US20240395408A1
公开(公告)日：2024-11-28
申请号：US18788009
申请日：2024-07-29
Applicant: ZHEJIANG LAB
Inventor： Jingsong LI , Peijun HU , Yu TIAN , Tianshu ZHOU
Abstract: A pancreatic postoperative diabetes prediction system based on supervised deep subspace learning. A deep convolutional neural network and the MITK software are used to obtain postoperative residual pancreas area, so as to taken as the region-of-interest. Traditional image radiomics features and deep semantic features are extracted from the residual pancreas area, and a high-dimensional image feature set is constructed. Clinical factors related to diabetes, including pancreatic excision rate, fat and muscle tissue components, demographic information and living habits are extracted, and a clinical feature set is constructed. Based on a supervised deep subspace learning network, image and clinical features are represented and fused in subspace in dimensionality reduction, while a prediction model is trained to mine sensitive features highly relevant to the prediction risk of a patient suffering postoperative diabetes mellitus with a high degree of automation and discriminative accuracy.
-
公开(公告)号：US20240212862A1
公开(公告)日：2024-06-27
申请号：US18595379
申请日：2024-03-04
Applicant: ZHEJIANG LAB
Inventor： Jingsong LI , Feng WANG , Hang ZHANG , Shengqiang CHI , Yu TIAN , Tianshu ZHOU
IPC: G16H50/50 , G06N3/0475 , G06N5/022
CPC classification number: G16H50/50 , G06N3/0475 , G06N5/022
Abstract: Disclosed is a general multi-disease prediction system based on causal check data generation. For a general scenario, the present invention provides a tendency score calculation method based on a general tendency score network from the perspective of causality; compared with the problem of poor interpretability of traditional generative adversarial networks, the present invention provides a generative adversarial network based on causal check, so that generated data better conforms to real causal logic; in view of the problem that existing graph convolutional neural networks are modeled only from the perspective of correlation, the present invention provides a general multi-disease prediction model based on a general causal graph convolutional neural network, and a causal effect value is integrated to improve the prediction performance of the general multi-disease prediction system on diseases, thereby solving the problems of poor model performance and low robustness caused by few training samples in a general scenario.
-
14.发明公开公开(公告)号：US20240184543A1
公开(公告)日：2024-06-06
申请号：US18525804
申请日：2023-11-30
Applicant: ZHEJIANG LAB
Inventor： Tianshu ZHOU , Xin GAO , Jingsong LI , Yu TIAN
Abstract: Disclosed is a page multiplexing method, a page multiplexing device, a storage medium and an electronic apparatus. After obtaining the page frame information of pages to be configured in a client to be developed, a component relational tree corresponding to the plurality of pages can be determined. The component relational tree is compared with a pre-constructed reference relational tree to determine a target tree structure composed of target components from the reference relational tree. Dependencies between target components in the reference relational tree match those in the component relational tree. The component code of the target component used by the developed client is queried to multiplex the component code. The component relational tree corresponding to pages to be developed can be compared with the reference relational tree corresponding to each page included in the developed client to determine the component code that can be multiplexed.
-
15.发明公开公开(公告)号：US20240145059A1
公开(公告)日：2024-05-02
申请号：US18364470
申请日：2023-08-02
Applicant: ZHEJIANG LAB
Inventor： Jingsong LI , Yu WANG , Shuang MA , Yu TIAN , Tianshu ZHOU
Abstract: Disclosed is a method and a system for discovering adverse drug reaction signals based on causal discovery. According to the present application, a causality is introduced in the process of discovering adverse drug reaction signals by using electronic medical record data, the data dimension in real-world electronic medical record data is maximally reserved, a Bayesian network structure containing causal effects, as well as a set of confounding factors which plays a role in both a medication intervention and an occurrence of an adverse event are constructed. The method of constructing the set of confounding factors starts from the data, without artificial access and prior knowledge, and retains the confounding factors in the real world to the greatest extent. A medication intervention group and a control group are constructed based on these confounding factors, and the randomized controlled trial is simulated.
-
Patent Agency Ranking
16.发明公开公开(公告)号：US20240078678A1
公开(公告)日：2024-03-07
申请号：US18360796
申请日：2023-07-27
Applicant: ZHEJIANG LAB
Inventor： Jingsong LI , Jun LI , Baochen WANG , Zhuoxin LI , Yu TIAN , Tianshu ZHOU
IPC: G06T7/00
CPC classification number: G06T7/0014 , G06T2207/10088 , G06T2207/30016
Abstract: The present application discloses a system and a device for functional connectivity matrix processing based on feature selection using a filtering method, which comprises the following steps: acquiring a preprocessed resting state brain functional magnetic resonance image of a subject; extracting time series; calculating a Pearson correlation coefficient to obtain a Pearson correlation coefficient matrix; vectorizing the Pearson correlation coefficient matrix; calculating quantitative correlation indices using a filtering method, and selecting a quantitative correlation index based on a preset threshold; performing weighting processing a selected functional connectivity feature by using the corresponding quantitative correlation index with high correlation with a disease diagnosis result to obtain a functional connectivity matrix; and obtaining a prediction result from the functional connectivity matrix.
-
公开(公告)号：US20240071607A1
公开(公告)日：2024-02-29
申请号：US18363701
申请日：2023-08-01
Applicant: ZHEJIANG LAB
Inventor： Jingsong LI , Wenchao XIANG , Guangyuan DENG , Tianshu ZHOU , Yu TIAN
CPC classification number: G16H40/20 , G06F9/4881 , G06F16/254 , G16H10/60
Abstract: The present disclosure discloses a medical ETL task dispatching method, system and apparatus based on multiple centers. The method includes following steps: step S1: testing and verifying ETL tasks; step S2: deploying the ETL tasks to a hospital center, and dispatching the ETL tasks to a plurality of executors for execution; step S3: screening an executor set meeting resource demands of ETL tasks to be dispatched; step S4: calculating a current task load of each executor in the executor set; step S5: selecting the executor with a minimum current task load to execute the ETL tasks; and step S6: selecting, by the dispatching machine, the ETL tasks from executor active queues according to a priority for execution. The present disclosure selects the most suitable executor by analyzing a serving index as a task to be dispatched on a current dispatching machine.
-
公开(公告)号：US20230409728A1
公开(公告)日：2023-12-21
申请号：US18336053
申请日：2023-06-16
Applicant: ZHEJIANG LAB
Inventor： Jingsong LI , Guangyuan DENG , Tianshu ZHOU , Yu TIAN
IPC: G06F21/62 , G06F16/901 , G06F21/60 , H04L9/30
CPC classification number: G06F21/6218 , G06F16/9024 , G06F21/602 , H04L9/3006
Abstract: Discloses a method and an apparatus for visual construction of a knowledge graph system. In the present disclosure, data permission of a distributed client is determined through a central server. The central server obtains a master template of a knowledge graph system and sends it to the distributed client. The distributed client receives a natural language inputted by a user and parses to generate an abstract syntax tree. The user completes customization of a subtemplate of the knowledge graph system through visual operation. The distributed client encrypts the subtemplate and then sends it to the central server. When the knowledge graph system is to be used, any knowledge concept is inputted, the central server calls and decrypts the subtemplate and then searches a database, and a tree structure knowledge graph is generated and sent to the distributed client.
-
19.发明公开公开(公告)号：US20240161251A1
公开(公告)日：2024-05-16
申请号：US18489876
申请日：2023-10-19
Applicant: ZHEJIANG LAB
Inventor： Jingsong LI , Jinnan HU , Peijun HU , Yu TIAN , Tianshu ZHOU
CPC classification number: G06T5/002 , G06T5/10 , G06T2207/20064 , G06T2207/20081 , G06T2207/20084
Abstract: Disclosed is an image denoising method and apparatus based on wavelet high-frequency channel synthesis. Image data are expanded to a plurality of frequency-domain channels, a plurality of “less-noise” channels and a plurality of “more-noise” channels are grouped through a noise-sort algorithm, and a denoising submodule and a synthesis submodule based on style transfer are combined to form a generative network. A discriminative network is established to add a constraint to the global loss function. After iteratively training the GAN model described above, the denoised image data can be obtained through wavelet inverse transformation. The disclosed algorithm can effectively solve the problem of “blurring” and “loss of details” introduced by traditional filtering or CNN-based deep learning methods, which is especially suitable for noise-overwhelmed image data or high dimensional image data.
-
公开(公告)号：US20240061993A1
公开(公告)日：2024-02-22
申请号：US18360794
申请日：2023-07-27
Applicant: ZHEJIANG LAB
Inventor： Tianshu ZHOU , Xin GAO , Jingsong LI , Yu TIAN
CPC classification number: G06F40/14 , G10L15/22 , G10L2015/223
Abstract: The present disclosure discloses a multi-component abstract association and fusion method and apparatus in page design. The method includes the following steps: step S1: a construction demand is acquired, and the construction demand is analyzed through a speech recognition method to obtain a natural language text; step S2: an abstract model is constructed by predefining a component library, a rule library and a relationship library, and the abstract model performs components fusion to obtain a JSON structure of a fused component; step S3: the JSON structure of the fused component is escaped into a virtual DOM by using a rendering function, and attributes and events of a virtual DOM node are mapped to obtain a fused component drawing result; and step S4: a real DOM structure is created and interpolated into a real DOM node, so as to realize display of the fused component on a view.
-
-
-
-
-
-
-
-
-
Search Results
24
records
(took 0.015 seconds)
