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Title:
METHOD FOR ESTABLISHING DEEP LEARNING-BASED MODEL FOR PREDICTING FUNCTIONS AFTER POST-CEREBRAL STROKE EARLY REHABILITATION
Document Type and Number:
WIPO Patent Application WO/2023/241012
Kind Code:
A1
Abstract:
A method for establishing a deep learning-based model for predicting functions after post-cerebral stroke early rehabilitation. By constructing a hybrid deep learning model consisting of a convolutional neural network (CNN) and a long short-term memory (LSTM) artificial neural network, and combining clinical data and early rehabilitation related data, the early and accurate prediction of function prognosis after post-cerebral ischemic stroke early rehabilitation is performed; long-term function prediction is performed in combination with a time-dependent modified Rankin scale (mRS), and at the same time, an individualized early rehabilitation strategy is formulated under guidance; function prediction can be performed in the early stage of cerebral stroke by means of the constructed machine learning-based prediction model for function prognosis after post-cerebral ischemic stroke early rehabilitation, i.e., a CNN-LSTM model, so that accurate guidance is provided for the formulation of a subsequent rehabilitation training plan, and the functions of a stroke patient are better recovered; moreover, medical resources can be conserved, and unnecessary consumption of labor and material resources is reduced.

Inventors:
LU XIAO (CN)
ZHENG YU (CN)
GU ZHAOHUA (CN)
GONG CHEN (CN)
LI JIAN (CN)
PENG LIJUN (CN)
Application Number:
PCT/CN2022/143730
Publication Date:
December 21, 2023
Filing Date:
December 30, 2022
Export Citation:
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Assignee:
UNIV NANJING MEDICAL (CN)
International Classes:
G16H10/20; G16H10/60; G16H20/10; G16H50/70
Domestic Patent References:
WO2018143540A12018-08-09
Foreign References:
CN115019919A2022-09-06
CN113988209A2022-01-28
CN111899894A2020-11-06
CN113808747A2021-12-17
CN114203295A2022-03-18
US20190246904A12019-08-15
Attorney, Agent or Firm:
NANJING TIANHUA PATENT AGENT CO., LTD. (CN)
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