Patents by Inventor Jianying Hu

Jianying Hu has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20250239344
    Abstract: A processor determines use duration for a medication of interest for providing patient treatment. Using a specified duration threshold, the processor performs a data linkage assessment on a data frame that includes at least covariates and medical outcome to determine data linkage between the covariates and the medical outcome, and the specified duration threshold. Based on the data linkage, the processor determines a linkage measure value that determines strength of an effect of taking the medication of interest, on the medical outcome. Until one or more stopping criteria is met, the processor performs an iterative processing of: performing of the data linkage assessment using different specified duration threshold and filtered data frame, and determining of the linkage measure value. Responsive to the one or more stopping criteria being met, the processor identifies the current iteration's specified duration threshold as a target use duration of the medication of interest.
    Type: Application
    Filed: January 22, 2024
    Publication date: July 24, 2025
    Inventors: Uri Kartoun, Jianying Hu, VIBHA Anand
  • Patent number: 12165398
    Abstract: The present disclosure relates to training method and apparatus for an object recognition model. There provides a training sample optimization apparatus for a neural network model for object recognition, comprising: for each training sample in a training sample database, a fluctuation determination unit configured to determine a fluctuation of model prediction of the training sample relative to a corresponding labeled identity of the training sample in a case of training the neural network model; and an optimization unit configured to determine whether the training sample can be used for training of the neural network model in the next training epoch, based on the fluctuation of the training sample.
    Type: Grant
    Filed: December 6, 2021
    Date of Patent: December 10, 2024
    Assignee: Canon Kabushiki Kaisha
    Inventors: Dongyue Zhao, Dongchao Wen, Xian Li, Weihong Deng, Jiani Hu
  • Patent number: 12026974
    Abstract: The present invention relates to method and apparatus for training a neural network for object recognition. A training method which includes inputting a training image set containing an object to be recognized, dividing the image samples in the training image set into simple samples and hard samples, for each kind of the image sample and the variation image sample, performing, a transitive transfer, calculating a distillation loss of the transferred student feature of the image sample relative to a teacher feature extracted from corresponding image sample of the other kind, classifying, the image sample, and calculating a classification loss of the image sample, calculating a total loss related to the training image set, and updating parameters of the neural network according to the calculated total loss.
    Type: Grant
    Filed: November 4, 2021
    Date of Patent: July 2, 2024
    Assignee: Canon Kabushiki Kaisha
    Inventors: Dongyue Zhao, Dongchao Wen, Xian Li, Weihong Deng, Jiani Hu
  • Patent number: 11947829
    Abstract: This application discloses a data writing method, device, a storage server and a computer readable storage medium, including: writing, when a write request is received, write data corresponding to the write request to a write buffer; acquiring historical access data of a data block corresponding to to-be-flushed data in the write buffer when a data flushing operation is triggered for the write buffer; determining whether the to-be-flushed data is write-only data based on the historical access data by using a pre-trained classifier; if yes, writing the to-be-flushed data to a hard disk drive; and if no, writing the to-be-flushed data to a cache. The data writing method provided by this application can effectively reduce the traffic of writing dirty data to the cache while reserving more space in the cache for the ordinary data, thereby improving the utilization of the cache space and the read hit rate of the cache.
    Type: Grant
    Filed: November 10, 2021
    Date of Patent: April 2, 2024
    Assignee: TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
    Inventors: Yu Zhang, Ke Zhou, Hua Wang, Jianying Hu, Yongguang Ji
  • Patent number: 11830625
    Abstract: Systems, computer-implemented methods, and computer program products to facilitate employing a probabilistic model to generate a continuous disease status index based on observational data are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a model component that employs a probabilistic model to generate probability distributions of disease states of a disease of an entity based on observational data of the entity. The computer executable components can further comprise an index component that generates a disease status index of the disease based on the probability distributions of the disease states.
    Type: Grant
    Filed: January 24, 2020
    Date of Patent: November 28, 2023
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Zhaonan Sun, Liuyi Yao, Zijun Yao, Jianying Hu
  • Publication number: 20220415486
    Abstract: A request to execute a sequentially randomized controlled trial (sRCT) that relates to a subject regarding a population of humans is received. Datapoints from the population that are needed for the sRCT and factors that define the population as fitting the sRCT are identified. It is detected that a human within an interaction satisfies the factors and therefore is part of the population. During the interaction, the datapoints from the human that are needed for the sRCT are gathered in response to detecting that the human is part of the population, and treatment is randomly assigned if the interaction is also a treatment decision point.
    Type: Application
    Filed: June 29, 2021
    Publication date: December 29, 2022
    Inventors: Zachary Shahn, Uri Kartoun, Daby Mousse Sow, Kenney Ng, Jianying Hu
  • Publication number: 20220415524
    Abstract: In an approach for building a machine learning model with a flexible prediction horizon, a processor gathers statistical data related to a disease from one or more regional sources. A processor clusters the statistical data according to a plurality of localized regional source similarity criteria and a plurality of region criteria. A processor builds a plurality of training models based on the clustered statistical data. A processor builds a plurality of feature vectors based on the plurality of localized regional source similarity criteria and the plurality of region criteria. A processor trains the plurality of training models separately against the plurality of feature vectors. A processor selects a best performing training model for each of the plurality of localized regional source similarity criteria and the plurality of region criteria based on a performance criterion. A processor tests the best performing training model to predict one or more future outcomes.
    Type: Application
    Filed: June 29, 2021
    Publication date: December 29, 2022
    Inventors: Sarah Kefayati, PRITHWISH CHAKRABORTY, Ajay Ashok Deshpande, Vishrawas Gopalakrishnan, Jianying Hu, Hu Trombley Huang, Gretchen Jackson, Xuan Liu, SAYALI NAVALEKAR, Raman Srinivasan
  • Publication number: 20220395786
    Abstract: The invention discloses a kind of thickening carbon dioxide displacement visual analog device, including pressure boost module, visual stirring vessel module and displacement analog module; the mentioned pressure boost module, visual stirring vessel module and displacement analog module are connected successively; the invention is used to develop the experimental study including evaluation of gas injection miscible-phase/non-miscible-phase displacement efficiency, percolation characteristics during gas displacement, mobility control technology during gas drive, and optimization of gas injection way.
    Type: Application
    Filed: May 20, 2022
    Publication date: December 15, 2022
    Inventors: Meilong Fu, Baofeng Hou, Jiani Hu
  • Patent number: 11410745
    Abstract: Techniques are described that facilitate determining potential cancer gene therapy targets by joint modeling of cancer survival events. In one embodiment, a computer-implemented comprises employing, by a device operatively coupled to a processor, a multi-task learning model to determine active genetic factors respectively associated with different types of cancer based on cancer survival data and patient genomic data for groups of patients that respectively survived the different types of cancer. The computer-implemented method further comprises, determining, by the device, common active genetic factors of the active genetic factors that are shared between two or more types of cancer of the different types of cancer.
    Type: Grant
    Filed: June 18, 2018
    Date of Patent: August 9, 2022
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Zhaonan Sun, Zach Shahn, Ping Zhang, Fei Wang, Jianying Hu
  • Publication number: 20220180627
    Abstract: The present disclosure relates to training method and apparatus for an object recognition model. There provides a training sample optimization apparatus for a neural network model for object recognition, comprising: for each training sample in a training sample database, a fluctuation determination unit configured to determine a fluctuation of model prediction of the training sample relative to a corresponding labeled identity of the training sample in a case of training the neural network model; and an optimization unit configured to determine whether the training sample can be used for training of the neural network model in the next training epoch, based on the fluctuation of the training sample.
    Type: Application
    Filed: December 6, 2021
    Publication date: June 9, 2022
    Inventors: Dongyue Zhao, Dongchao Wen, Xian Li, Weihong Deng, Jiani Hu
  • Publication number: 20220138454
    Abstract: The present invention relates to method and apparatus for training a neural network for object recognition. A training method which includes inputting a training image set containing an object to be recognized, dividing the image samples in the training image set into simple samples and hard samples, for each kind of the image sample and the variation image sample, performing, a transitive transfer, calculating a distillation loss of the transferred student feature of the image sample relative to a teacher feature extracted from corresponding image sample of the other kind, classifying, the image sample, and calculating a classification loss of the image sample, calculating a total loss related to the training image set, and updating parameters of the neural network according to the calculated total loss.
    Type: Application
    Filed: November 4, 2021
    Publication date: May 5, 2022
    Inventors: Dongyue Zhao, Dongchao Wen, Xian Li, Weihong Deng, Jiani Hu
  • Patent number: 11309063
    Abstract: Embodiments of the present invention are directed to a computer-implemented method for generating a framework for analyzing adverse drug reactions. A non-limiting example of the computer-implemented method includes receiving to a processor, a plurality of drug chemical structures. The non-limiting example also includes receiving, to the processor, a plurality of known drug-adverse drug reaction associations. The non-limiting example also includes constructing, by the processor, a deep learning framework for each of a plurality of adverse drug reactions based at least in part upon the plurality of drug chemical structures and the plurality of known adverse-drug reaction associations.
    Type: Grant
    Filed: November 16, 2017
    Date of Patent: April 19, 2022
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Sanjoy Dey, Achille Belly Fokoue-Nkoutche, Jianying Hu, Heng Luo, Ping Zhang
  • Patent number: 11289178
    Abstract: Embodiments of the present invention are directed to a computer-implemented method for generating a framework for analyzing adverse drug reactions. A non-limiting example of the computer-implemented method includes receiving to a processor, a plurality of drug chemical structures. The non-limiting example also includes receiving, to the processor, a plurality of known drug-adverse drug reaction associations. The non-limiting example also includes constructing, by the processor, a deep learning framework for each of a plurality of adverse drug reactions based at least in part upon the plurality of drug chemical structures and the plurality of known adverse-drug reaction associations.
    Type: Grant
    Filed: April 21, 2017
    Date of Patent: March 29, 2022
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Sanjoy Dey, Achille Belly Fokoue-Nkoutche, Jianying Hu, Heng Luo, Ping Zhang
  • Publication number: 20220066691
    Abstract: This application discloses a data writing method, device, a storage server and a computer readable storage medium, including: writing, when a write request is received, write data corresponding to the write request to a write buffer; acquiring historical access data of a data block corresponding to to-be-flushed data in the write buffer when a data flushing operation is triggered for the write buffer; determining whether the to-be-flushed data is write-only data based on the historical access data by using a pre-trained classifier; if yes, writing the to-be-flushed data to a hard disk drive; and if no, writing the to-be-flushed data to a cache. The data writing method provided by this application can effectively reduce the traffic of writing dirty data to the cache while reserving more space in the cache for the ordinary data, thereby improving the utilization of the cache space and the read hit rate of the cache.
    Type: Application
    Filed: November 10, 2021
    Publication date: March 3, 2022
    Inventors: Yu ZHANG, Ke ZHOU, Hua WANG, Jianying HU, Yongguang JI
  • Publication number: 20220036984
    Abstract: A system (or method) for generation and employment of disease progression model(s) that facilitates identifying and indexing discriminative features for disease progression in observational data. The disease progression prediction system comprises a processor that executes computer executable components stored in memory. A receiving component receives and learns observational patient data. A model generation component builds a preliminary disease progression model. An identification component identifies discriminative clinical features for different disease stages. A ranking component ranks discriminative powers of clinical features for respective pairs of disease stages; wherein the model generation component employs the ranked features to generate a final disease progression model.
    Type: Application
    Filed: October 15, 2021
    Publication date: February 3, 2022
    Inventors: Yu Cheng, Soumya Ghosh, Jianying Hu, Ying Li, Zhaonan Sun
  • Patent number: 11200451
    Abstract: A template determining apparatus including an attribute distribution determination unit configured to determine a distribution of a specific attribute in a plurality of images; and a template determination unit configured to adaptatively determine a template set from the plurality of images according to the determined distribution of the specific attribute of the plurality of images. Where the determined template set will be used for image normalization.
    Type: Grant
    Filed: November 11, 2019
    Date of Patent: December 14, 2021
    Assignee: Canon Kabushiki Kaisha
    Inventors: Yaohai Huang, Jianteng Peng, Weihong Deng, Jiani Hu
  • Patent number: 11195133
    Abstract: Systems and methods for individual risk factor identification include identifying common risk factors for one or more risk targets from population data. Individuals are stratified into clusters based upon the common risk factors. A discriminability of each of the common risk factors is determined, using a processor, for a target cluster using individual data of the target cluster to provide re-ranked common risk factors as individual risk factors for the target cluster, such that the discriminability is a measure of how a risk factor discriminates its cluster from other clusters.
    Type: Grant
    Filed: May 9, 2018
    Date of Patent: December 7, 2021
    Assignee: International Business Machines Corporation
    Inventors: David H. Gotz, Pei-Yun S. Hsueh, Jianying Hu, Jimeng Sun
  • Patent number: 11177024
    Abstract: A system (or method) for generation and employment of disease progression model(s) that facilitates identifying and indexing discriminative features for disease progression in observational data. The disease progression prediction system comprises a processor that executes computer executable components stored in memory. A receiving component receives and learns observational patient data. A model generation component builds a preliminary disease progression model. An identification component identifies discriminative clinical features for different disease stages. A ranking component ranks discriminative powers of clinical features for respective pairs of disease stages; wherein the model generation component employs the ranked features to generate a final disease progression model.
    Type: Grant
    Filed: October 31, 2017
    Date of Patent: November 16, 2021
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Yu Cheng, Soumya Ghosh, Jianying Hu, Ying Li, Zhaonan Sun
  • Publication number: 20210241097
    Abstract: A training method and device for an object recognition model. An apparatus for optimizing a neural network model for object recognition, including a loss determination unit configured to determine loss data for features extracted from a training image set using the neural network model and a loss function with a weight function, and an updating unit configured to perform an updating operation on parameters of the neural network model based on the loss data and an updating function, wherein the updating function is derived based on the loss function with the weight function of the neural network model, and the weight function and the loss function change monotonically in a specific value interval in the same direction.
    Type: Application
    Filed: November 4, 2020
    Publication date: August 5, 2021
    Inventors: Dongyue Zhao, Dongchao Wen, Xian Li, Weihong Deng, Jiani Hu
  • Publication number: 20210233662
    Abstract: Systems, computer-implemented methods, and computer program products to facilitate employing a probabilistic model to generate a continuous disease status index based on observational data are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a model component that employs a probabilistic model to generate probability distributions of disease states of a disease of an entity based on observational data of the entity. The computer executable components can further comprise an index component that generates a disease status index of the disease based on the probability distributions of the disease states.
    Type: Application
    Filed: January 24, 2020
    Publication date: July 29, 2021
    Inventors: Zhaonan Sun, Liuyi Yao, Zijun Yao, Jianying Hu