公开(公告)号：US11663248B2

公开(公告)日：2023-05-30

申请号：US17302385

申请日：2021-04-30

Applicant: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.

Inventor： Dongwei Zhu ,  Haifeng Huang ,  Chao Lu ,  Jialin Wu ,  Yuan Xia ,  Xueying Shi ,  Xiaoqin Li ,  Xiaoming Hu

IPC: G06F16/335 ,  G06F16/34 ,  G06F16/338 ,  G06F16/332 ,  G06Q30/0203

CPC classification number: G06F16/3326 ,  G06F16/335 ,  G06F16/338 ,  G06F16/34 ,  G06Q30/0203

Abstract: Embodiments of the present disclosure provide a method and apparatus for processing consultation information. A specific implementation of the method includes: pushing, in response to receiving consultation information of a first user, a questionnaire corresponding to the consultation information to the first user; acquiring a questionnaire result corresponding to the questionnaire and submitted by the first user; inputting the questionnaire result into a preset consultation model, to obtain a first consultation result; pushing the questionnaire result and the first consultation result to a second user; and in response to receiving a second consultation result provided by the second user based on the questionnaire result and the first consultation result, pushing the second consultation result to the first user.

公开(公告)号：US20210407642A1

公开(公告)日：2021-12-30

申请号：US17108367

申请日：2020-12-01

Applicant: Beijing Baidu Netcom Science and Technology Co., Ltd.

Inventor： Yuan Xia ,  Zhenhui Shi ,  Chao Lu ,  Haifeng Huang

IPC: G16H20/10 ,  G16H70/40 ,  G16H10/60 ,  G06F40/205

Abstract: A drug recommendation method and device, an electronic apparatus, and a storage medium are provided, which are related to the fields of artificial intelligence deep learning technology, intelligent recommendation, and knowledge graph. The specific implementation includes: acquiring related information of a target object; and determining drug recommendation information for the target object based on the related information of the target object and a first model, where the drug recommendation information contains information of at least one drug, where the first model is a model obtained by performing iterative processing on output information of a second model, and the second model is used for evaluating drug recommendation information output by the first model during the iterative processing, to obtain an evaluation result of the drug recommendation information.