Diabetes patient blood glucose management method and system based on reinforcement learning, medium and terminal
The invention provides a diabetes patient blood glucose management method and system based on reinforcement learning, a medium and a terminal. The method comprises the following steps: training a decision network model based on a reinforcement learning algorithm to obtain a trained decision network...
Saved in:
Main Authors | , , , , , , |
---|---|
Format | Patent |
Language | Chinese English |
Published |
04.06.2021
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | The invention provides a diabetes patient blood glucose management method and system based on reinforcement learning, a medium and a terminal. The method comprises the following steps: training a decision network model based on a reinforcement learning algorithm to obtain a trained decision network model; acquiring current state information of a diabetes patient; and sending the current state information to the trained decision network model, so that the trained decision network model determines the insulin injection amount corresponding to the diabetes patient at the next future moment based on the current state information, and blood glucose management of the diabetic patient is achieved. According to the method, the decision network model is trained by a reinforcement learning algorithm based on historical blood sugar data and future carbohydrate intake of the diabetes patient, so that the relationship between carbohydrate and blood sugar change is utilized from historical information of the diabetes patie |
---|---|
AbstractList | The invention provides a diabetes patient blood glucose management method and system based on reinforcement learning, a medium and a terminal. The method comprises the following steps: training a decision network model based on a reinforcement learning algorithm to obtain a trained decision network model; acquiring current state information of a diabetes patient; and sending the current state information to the trained decision network model, so that the trained decision network model determines the insulin injection amount corresponding to the diabetes patient at the next future moment based on the current state information, and blood glucose management of the diabetic patient is achieved. According to the method, the decision network model is trained by a reinforcement learning algorithm based on historical blood sugar data and future carbohydrate intake of the diabetes patient, so that the relationship between carbohydrate and blood sugar change is utilized from historical information of the diabetes patie |
Author | WANG YUE SHI YIQI ZHAO QINPEI WANG CONGRONG LI JIANGFENG RAO WEIXIONG ZHU JINHAO |
Author_xml | – fullname: WANG CONGRONG – fullname: LI JIANGFENG – fullname: ZHAO QINPEI – fullname: ZHU JINHAO – fullname: WANG YUE – fullname: SHI YIQI – fullname: RAO WEIXIONG |
BookMark | eNqNizsOwjAQBVNAwe8OSw8SgSBBiQKIioo-2sQvwZK9tmxTcHvC5wBUU8zMOBuIE4wyf9RcIyGS56QhiWrjnKLOPBoXQZaFO9i3sEj33rAois-YYKnmCEVOKEBL60LzDQ04iJZu0S9KP-xnSQhWC5tpNmzZRMx-nGTz8-lWXpbwrkL03ECQqvKa5-v9alcU28Pmn-YF1yJFQA |
ContentType | Patent |
DBID | EVB |
DatabaseName | esp@cenet |
DatabaseTitleList | |
Database_xml | – sequence: 1 dbid: EVB name: esp@cenet url: http://worldwide.espacenet.com/singleLineSearch?locale=en_EP sourceTypes: Open Access Repository |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Medicine Chemistry Sciences Physics |
DocumentTitleAlternate | 基于强化学习的糖尿病患者血糖管理方法、系统、介质及终端 |
ExternalDocumentID | CN112908445A |
GroupedDBID | EVB |
ID | FETCH-epo_espacenet_CN112908445A3 |
IEDL.DBID | EVB |
IngestDate | Fri Jul 19 14:49:18 EDT 2024 |
IsOpenAccess | true |
IsPeerReviewed | false |
IsScholarly | false |
Language | Chinese English |
LinkModel | DirectLink |
MergedId | FETCHMERGED-epo_espacenet_CN112908445A3 |
Notes | Application Number: CN202110193477 |
OpenAccessLink | https://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210604&DB=EPODOC&CC=CN&NR=112908445A |
ParticipantIDs | epo_espacenet_CN112908445A |
PublicationCentury | 2000 |
PublicationDate | 20210604 |
PublicationDateYYYYMMDD | 2021-06-04 |
PublicationDate_xml | – month: 06 year: 2021 text: 20210604 day: 04 |
PublicationDecade | 2020 |
PublicationYear | 2021 |
RelatedCompanies | SHANGHAI NO.4 PEOPLE'S HOSPITAL |
RelatedCompanies_xml | – name: SHANGHAI NO.4 PEOPLE'S HOSPITAL |
Score | 3.4656258 |
Snippet | The invention provides a diabetes patient blood glucose management method and system based on reinforcement learning, a medium and a terminal. The method... |
SourceID | epo |
SourceType | Open Access Repository |
SubjectTerms | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS PHYSICS |
Title | Diabetes patient blood glucose management method and system based on reinforcement learning, medium and terminal |
URI | https://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20210604&DB=EPODOC&locale=&CC=CN&NR=112908445A |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfZ1bS8MwFMcPc17fdCo6L0SQPlkcbZplD0VcujIEuyFT9jbaNPWC68baIfjpTbJs80VfkzaQU05O0vzO_wBcp47b8mJPSE9ziI0FiW2Kk8zOSOZwt-kmTaFpi4h0n_HD0BtW4GOZC6N1Qr-0OKL0KC79vdTr9XT9EyvQbGVxm7zLpsldOPADy5yO5fmFyI8etP1Ovxf0mMWYzyIrevLVtqJBMfbuN2BTbaOVzn7npa2yUqa_Q0q4D1t9OVpeHkDl-60Gu2xZea0GO4_mwrsG25rQ5IVsNF5YHMLUYCwFMqqoSOPnyODnaLxCWtCiQDSK8xQtNJuRClspmuRoJrRoKl88aKpHvN4gdds-H-tXDCnzeQRXYWfAuracxGhlsRGL1vN1j6GaT3JxAoinrabKVPV4THHWEpQQ0SBZQp00oZx6p1D_e5z6f51nsKesrxkqfA7VcjYXFzJal8mlNvMPa9-bdQ |
link.rule.ids | 230,309,786,891,25594,76906 |
linkProvider | European Patent Office |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfZ1bT8IwFMdPEC_4pqhRvNXE8OQi2bquPCxGOgkqDGLQ8EZ26bxEBmEjJn5621LAF33t2iZtc3Z6-Z3_AbiMTatuBzYXlmYSA3MSGBSHiZGQxIwsxwodrmgLn7Se8cPAHhTgYxELo3RCv5Q4orCoSNh7rv7Xk9UllqfYyuw6fBdF45tm3_Wq-nQszi9ELLrXcO96Xa_Lqoy5zK_6T67cVtQoxvbtGqw7Up1Xbp1eGjIqZfLbpTR3YKMnekvzXSh8v5WhxBaZ18qw1dEP3mXYVIRmlIlCbYXZHkw0xpIhrYqKFH6ONH6ORkukBc0TRKMgjdFcsxlJtxWjcYqmXImmRvOKOnvE6xWSr-2zkWqiSZnPfbho3vVZyxCDGC5nbMj81XitAyim45QfAoriuiMjVe0ooDipc0oIr5EkpGYc0ojaR1D5u5_Kfx_PodTqd9rD9r3_eAzbciUUT4VPoJhPZ_xUeO48PFNT_gPbGp5i |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Apatent&rft.title=Diabetes+patient+blood+glucose+management+method+and+system+based+on+reinforcement+learning%2C+medium+and+terminal&rft.inventor=WANG+CONGRONG&rft.inventor=LI+JIANGFENG&rft.inventor=ZHAO+QINPEI&rft.inventor=ZHU+JINHAO&rft.inventor=WANG+YUE&rft.inventor=SHI+YIQI&rft.inventor=RAO+WEIXIONG&rft.date=2021-06-04&rft.externalDBID=A&rft.externalDocID=CN112908445A |