公开(公告)号：US20250014748A1

公开(公告)日：2025-01-09

申请号：US18347237

申请日：2023-07-05

Applicant: IQVIA Inc.

Inventor： Tong Wu ,  Yong Cai ,  Yunlong Wang ,  Fan Zhang ,  Emily Zhao ,  Yilian Yuan

IPC: G16H50/20 ,  G16H50/70

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating data structures from graphs. The computer accesses a graph having patient nodes representing patients and patient health data nodes representing health data for patients, the nodes being connected by edges. The computer generates subgraphs by identifying patient nodes and patient health data nodes associated with a particular healthcare provider. The computer generates, by a subgraph neural network, a healthcare provider data structure for a respective subgraph. The computer generates, by a first graph neural network, patient data structures for a respective patient graph network and health data structures for a respective health data graph network. Each healthcare provider data structure, patient graph network, health data structure, has a lower dimension than the corresponding subgraph, patient graph network, and health data graph network, respectively. The computer provides at least one of the data structures to a model.

公开(公告)号：US10937531B1

公开(公告)日：2021-03-02

申请号：US15948006

申请日：2018-04-09

Applicant: IQVIA Inc.

Inventor： Yunlong Wang ,  Emily Zhao ,  Yilian Yuan ,  Anthony Michael Wojeck ,  Robert Doyle ,  Yong Cai

IPC: G16H20/10 ,  G16H80/00 ,  G16H10/60

Abstract: A computer-assisted method to provide timely multi-channel notification of treatments to healthcare providers and patients, the method including receiving de-identified longitudinal medical records, treatment prescription records of healthcare providers, and notification data. Relationships between the healthcare providers, the anonymized patients, and the notifications are identified using the de-identified longitudinal medical records, the treatment prescription records of the healthcare providers, and the notification data. An impact of notifications being received by both the healthcare provider for the anonymized patient and the anonymized patient on whether the anonymized patient received the treatment is determined. A plan to timely provide notifications of treatments to the healthcare provider and the anonymized patients is determined based at least on the impact of the notifications being received by both the healthcare provider for the anonymized patient and the anonymized patient on whether the anonymized patient received the treatment.

公开(公告)号：USRE49853E1

公开(公告)日：2024-02-27

申请号：US17892830

申请日：2022-08-22

Applicant: IQVIA Inc.

Inventor： Yong Cai ,  Bob Doyle ,  George Mu ,  Dong Dai ,  Emily Zhao ,  Steven Rosztoczy

IPC: G16H40/20 ,  G16H50/70 ,  G06N20/00 ,  G06F21/62

CPC classification number: G16H40/20 ,  G06F21/6254 ,  G06N20/00 ,  G16H50/70

Abstract: A computer-assisted method to timely provide notifications of treatments, the method including receiving de-identified longitudinal medical records, receiving notification data, identifying anonymized patients that received the treatment, identifying notifications for the treatment that were received by the recipients, determining, for each of the identified notifications, whether the recipient is an anonymized patient identified as having received the treatment, determining, for each of the identified notifications for the treatment determined to be received by a recipient that is an anonymized patient identified as having received the treatment, a time relationship between the time when the treatment was received by the anonymized patient and the time that the notification was received by the recipient that is the anonymized patient, and determining, for each of the anonymized patients that received the treatment, associations between one or more time relationships for notifications received by the anonymized patient.

公开(公告)号：US12079719B1

公开(公告)日：2024-09-03

申请号：US17003127

申请日：2020-08-26

Applicant: IQVIA Inc.

Inventor： Guanhao Wei ,  Yunlong Wang ,  Li Zhou ,  Lynn Lu ,  Emily Zhao ,  Lishan Feng ,  Fan Zhang ,  Frank Jing ,  Yilian Yuan

IPC: G06N3/08 ,  G06N3/044 ,  G06N3/045 ,  G06N3/047 ,  G06N3/048 ,  G06N5/01 ,  G06N20/20 ,  G16H10/60 ,  G16H40/20 ,  G16H50/70 ,  G16H70/20 ,  G16H70/40 ,  G16H70/60

CPC classification number: G06N3/08 ,  G06N3/044 ,  G06N3/045 ,  G06N3/047 ,  G06N3/048 ,  G06N5/01 ,  G06N20/20 ,  G16H10/60 ,  G16H40/20 ,  G16H50/70 ,  G16H70/20 ,  G16H70/40 ,  G16H70/60

Abstract: A deep learning model implements continuous, lifelong machine learning (LML) based on a Bayesian neural network using an inventive framework including wide, deep, and prior components that employ diverse algorithms to leverage available real-world healthcare data differently to improve prediction performance. The outputs from each component of the framework are fed into a wide and shallow neural network and the posterior structure of the final model output may be utilized as a prior structure when the deep learning model is refreshed with new data in a deep learning process. Lifelong learning is implemented by dynamically integrating present learning from the wide and deep learning components with past learning from traditional tree models in the prior component into future predictions. Thus, the present Bayesian deep neural network-based LML model increases accuracy in identifying patient profiles by continuously learning, as new data become available, without forgetting prior knowledge.

公开(公告)号：US11923074B2

公开(公告)日：2024-03-05

申请号：US17174705

申请日：2021-02-12

Applicant: IQVIA Inc.

Inventor： Ruoxin Li ,  Yong Cai ,  John H. Eichert, Jr. ,  Emily Zhao ,  Yilian Yuan ,  Yanping Liu ,  Steve Eichert ,  D. Bruce West ,  William McClellan

IPC: G16H40/20 ,  G06N3/045 ,  G06N3/08

CPC classification number: G16H40/20 ,  G06N3/045 ,  G06N3/08

Abstract: Embodiments of the present disclosure provide a method for identifying those entities within a network that have the most influence on other entities within the network. A multi-relational network comprising links among a plurality of physicians is generated based on peer network data, wherein each link indicates a first physician that influences a second physician, and a weight of the influence. A decision by a treating physician of the plurality of physicians is decomposed, using a deep learning engine, into a magnitude of peer influence and a magnitude of control factor influence based on the multi-relational network and a plurality of control factors respectively. The magnitude of peer influence among one or more physicians in the multi-relational network is distributed among physicians in the multi-relational network based on the links each physician maintains with other physicians.

公开(公告)号：US11996173B1

公开(公告)日：2024-05-28

申请号：US16813213

申请日：2020-03-09

Applicant: IQVIA Inc.

Inventor： Yong Cai ,  Bob Doyle ,  Dong Dai ,  Wenzhe Lu ,  Emily Zhao ,  Steven Rosztoczy

IPC: G16H10/60 ,  G06N3/088 ,  G16H50/70

CPC classification number: G16H10/60 ,  G06N3/088 ,  G16H50/70

Abstract: A computer-assisted method to timely provide notifications of treatments, the method including receiving de-identified longitudinal medical records, each de-identified longitudinal medical record representing a record of a different anonymized patient and encoding information identifying a treatment received by the anonymized patient and receiving notification data including notification records, each notification record encoding information identifying a channel through which the notification was provided. The method includes determining a first channel impact model representing an impact of a notification provided through a first channel on a treatment being received, a second channel impact model representing an impact of a notification provided through a second channel on a treatment being received, and determining a multi-channel impact model representing an impact of notifications being provided through both the first channel and the second channel on a treatment being received.

公开(公告)号：US20220262499A1

公开(公告)日：2022-08-18

申请号：US17174705

申请日：2021-02-12

Applicant: IQVIA, INC.

Inventor： Ruoxin Li ,  Yong Cai ,  John H. Eichert, JR. ,  Emily Zhao ,  Yilian Yuan ,  Yanping Liu ,  Steve Eichert ,  D. Bruce West ,  William McClellan

IPC: G16H40/20 ,  G06N3/08 ,  G06N3/04

Abstract: Embodiments of the present disclosure provide a method for identifying those entities within a network that have the most influence on other entities within the network. A multi-relational network comprising links among a plurality of physicians is generated based on peer network data, wherein each link indicates a first physician that influences a second physician, and a weight of the influence. A decision by a treating physician of the plurality of physicians is decomposed, using a deep learning engine, into a magnitude of peer influence and a magnitude of control factor influence based on the multi-relational network and a plurality of control factors respectively. The magnitude of peer influence among one or more physicians in the multi-relational network is distributed among physicians in the multi-relational network based on the links each physician maintains with other physicians.

公开(公告)号：US11328825B1

公开(公告)日：2022-05-10

申请号：US16847562

申请日：2020-04-13

Applicant: IQVIA Inc.

Inventor： Kezi Yu ,  Fan Zhang ,  Yunlong Wang ,  Yilian Yuan ,  Emily Zhao ,  William McClellan ,  Yong Cai

IPC: G16H50/70 ,  G16H10/60 ,  G16H40/20 ,  G16H50/20 ,  G16H20/10 ,  A61B5/00

Abstract: Systems and techniques are disclosed for using machine-learning to identify potential opportunity patients that are more likely to adjust his/her preference for a healthcare provider or service. In some implementations, integrated patient data is obtained. A patient sequence feature vector, a provider sequence feature vector, and a set of entity-specific feature vectors are generated. A set of opportunity patients is identified. A notification is transmitted to the set of opportunity patients about a second treatment plan.