公开(公告)号：US11710571B2

公开(公告)日：2023-07-25

申请号：US17264299

申请日：2019-08-30

申请人： PING AN TECHNOLOGY (SHENZHEN) CO., LTD.

发明人： Wenxiao Jia ,  Kewei Tan ,  Xiang Li ,  Guotong Xie

IPC分类号： G16H50/50 ,  G06N3/0442 ,  G16H50/20 ,  G16H50/30 ,  G06N3/045

CPC分类号： G16H50/50 ,  G06N3/045 ,  G06N3/0442 ,  G16H50/20 ,  G16H50/30

摘要： A long short-term memory (LSTM) model-based disease prediction method and apparatus, a computer device, and a storage medium are provided. The method includes: obtaining first medical data of a target object and second medical data of an associated object; inputting the first medical data and the second medical data into a first LSTM network in the LSTM model, to obtain a hidden state vector sequence in the first LSTM network; inputting the hidden state vector sequence into a second LSTM network for operation, to obtain a disease prediction result; selecting a predicted disease with an incidence rate higher than a preset threshold, and recording the predicted disease as a designated disease, and obtaining, based on a preset disease association network, an associated disease directly connected to the designated disease; and outputting the disease prediction result and the associated disease, thereby improving the prediction accuracy.

公开(公告)号：US20210296002A1

公开(公告)日：2021-09-23

申请号：US17264299

申请日：2019-08-30

申请人： PING AN TECHNOLOGY (SHENZHEN) CO., LTD.

发明人： Wenxiao Jia ,  Kewei Tan ,  Xiang Li ,  Guotong Xie

IPC分类号： G16H50/50

摘要： A long short-term memory (LSTM) model-based disease prediction method and apparatus, a computer device, and a storage medium are provided. The method includes: obtaining first medical data of a target object and second medical data of an associated object; inputting the first medical data and the second medical data into a first LSTM network in the LSTM model, to obtain a hidden state vector sequence in the first LSTM network; inputting the hidden state vector sequence into a second LSTM network for operation, to obtain a disease prediction result; selecting a predicted disease with an incidence rate higher than a preset threshold, and recording the predicted disease as a designated disease, and obtaining, based on a preset disease association network, an associated disease directly connected to the designated disease; and outputting the disease prediction result and the associated disease, thereby improving the prediction accuracy.