公开(公告)号：US20190384889A1

公开(公告)日：2019-12-19

申请号：US16011231

申请日：2018-06-18

Applicant: International Business Machines Corporation

Inventor： Zhaonan Sun ,  Zach Shahn ,  Ping Zhang ,  Fei Wang ,  Jianying Hu

IPC: G06F19/12 ,  G06F19/18 ,  G16H50/30 ,  G16H10/60

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.

公开(公告)号：US11177024B2

公开(公告)日：2021-11-16

申请号：US15799664

申请日：2017-10-31

Applicant: International Business Machines Corporation

Inventor： Yu Cheng ,  Soumya Ghosh ,  Jianying Hu ,  Ying Li ,  Zhaonan Sun

IPC: G16H10/60 ,  G16H50/50 ,  G06Q10/10

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.

公开(公告)号：US10535424B2

公开(公告)日：2020-01-14

申请号：US15048413

申请日：2016-02-19

Applicant: International Business Machines Corporation

Inventor： Jianying Hu ,  Zhaonan Sun ,  Fei Wang

IPC: G16H10/60 ,  G16H50/30 ,  G16H50/50 ,  G16H50/70

Abstract: An apparatus, method and computer program product for proactive comprehensive generic risk screening. The method performs proactive comprehensive generic risk screening by implementing steps of training comprising steps of receiving cross domain risks and features, optimizing linkage regularization using the received features and the received cross domain risks, said linkage regularization comprising multi-task predictive model training, feature selection and ranking, risk association learning and risk association selection, and outputting patient risk scores, identified high risk patients, risk factors for risks and risk groups, and risk groups and risk associations and calculating risk score for an individual patient comprising steps of receiving individual features comprising patient information, performing said linkage regularization using the received individual features and outputting patient risk scores for said individual patient, and high risk for said individual patient. The calculating risk score can be performed for more than one patient.

公开(公告)号：US20190034595A1

公开(公告)日：2019-01-31

申请号：US15661591

申请日：2017-07-27

Applicant: International Business Machines Corporation

Inventor： Zhaonan Sun ,  Soumya Ghosh ,  Ying Li ,  Yu Cheng ,  Jianying Hu

IPC: G06F19/00

Abstract: Embodiments describing an approach to receiving patient registry data and creating at least one control model based on the patient registry data. Transforming patient registry data into at least one prediction confident interval based on the at least one control model. Transforming the at least one prediction confident interval into at least one robust assessment score, and outputting the at least one robust assessment score for measuring disease progression indicators.