Method and means for postprandial blood glucose level prediction

The invention relates to a method (100) for predicting blood glucose levels, in particular for postprandial blood glucose level prediction, the method being computer-implemented and comprising: receiving (101) a first medical data set of a patient covering a time range, said first medical data set c...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: REITERER Florian, ADELBERGER Daniel, SCHRANGL Patrick, RINGEMANN Christian, DEL RE Luigi
Format: Patent
Sprache:eng ; heb
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title
container_volume
creator REITERER Florian
ADELBERGER Daniel
SCHRANGL Patrick
RINGEMANN Christian
DEL RE Luigi
description The invention relates to a method (100) for predicting blood glucose levels, in particular for postprandial blood glucose level prediction, the method being computer-implemented and comprising: receiving (101) a first medical data set of a patient covering a time range, said first medical data set comprising glucose data and further other medical data of said patient, extracting (102) a second medical data set from said first medical data set, wherein the second medical data set is a subset of the first medical data set and wherein the extracting comprises at least one of: identifying (103) duplicates in the first medical data set and removing identified duplicates, identifying (104) data values that lie above a predefined maximum threshold data value or identifying (105) data values that lie below a predefined minimum threshold data value and removing data associated to said identified data values, identifying (106) data values that differ from predetermined expected data values by more than a predetermined amount and removing data associated to said identified data values, identifying (107) incomplete data for which data values are missing and removing identified incomplete data, identifying (108) at least one predetermined time-dependent data pattern and removing data associated to said identified time-dependent data pattern, providing (109) the extracted second medical data set as input to a blood glucose level prediction model, and predicting (110) future blood glucose levels of the patient using the output of the blood glucose level prediction model based on the second medical data set.
format Patent
fullrecord <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_IL306089A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>IL306089A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_IL306089A3</originalsourceid><addsrcrecordid>eNrjZHDwTS3JyE9RSMxLUchNTcwrVkjLL1IoyC8uKSgCimUm5igk5eQDFaTnlCbnF6cq5KSWpeYoFBSlpmQml2Tm5_EwsKYl5hSn8kJpbgY5N9cQZw_d1IL8-NTigsTk1LzUknhPH2MDMwMLS0djggoAtmwwSA</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Method and means for postprandial blood glucose level prediction</title><source>esp@cenet</source><creator>REITERER Florian ; ADELBERGER Daniel ; SCHRANGL Patrick ; RINGEMANN Christian ; DEL RE Luigi</creator><creatorcontrib>REITERER Florian ; ADELBERGER Daniel ; SCHRANGL Patrick ; RINGEMANN Christian ; DEL RE Luigi</creatorcontrib><description>The invention relates to a method (100) for predicting blood glucose levels, in particular for postprandial blood glucose level prediction, the method being computer-implemented and comprising: receiving (101) a first medical data set of a patient covering a time range, said first medical data set comprising glucose data and further other medical data of said patient, extracting (102) a second medical data set from said first medical data set, wherein the second medical data set is a subset of the first medical data set and wherein the extracting comprises at least one of: identifying (103) duplicates in the first medical data set and removing identified duplicates, identifying (104) data values that lie above a predefined maximum threshold data value or identifying (105) data values that lie below a predefined minimum threshold data value and removing data associated to said identified data values, identifying (106) data values that differ from predetermined expected data values by more than a predetermined amount and removing data associated to said identified data values, identifying (107) incomplete data for which data values are missing and removing identified incomplete data, identifying (108) at least one predetermined time-dependent data pattern and removing data associated to said identified time-dependent data pattern, providing (109) the extracted second medical data set as input to a blood glucose level prediction model, and predicting (110) future blood glucose levels of the patient using the output of the blood glucose level prediction model based on the second medical data set.</description><language>eng ; heb</language><subject>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</subject><creationdate>2023</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20231101&amp;DB=EPODOC&amp;CC=IL&amp;NR=306089A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20231101&amp;DB=EPODOC&amp;CC=IL&amp;NR=306089A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>REITERER Florian</creatorcontrib><creatorcontrib>ADELBERGER Daniel</creatorcontrib><creatorcontrib>SCHRANGL Patrick</creatorcontrib><creatorcontrib>RINGEMANN Christian</creatorcontrib><creatorcontrib>DEL RE Luigi</creatorcontrib><title>Method and means for postprandial blood glucose level prediction</title><description>The invention relates to a method (100) for predicting blood glucose levels, in particular for postprandial blood glucose level prediction, the method being computer-implemented and comprising: receiving (101) a first medical data set of a patient covering a time range, said first medical data set comprising glucose data and further other medical data of said patient, extracting (102) a second medical data set from said first medical data set, wherein the second medical data set is a subset of the first medical data set and wherein the extracting comprises at least one of: identifying (103) duplicates in the first medical data set and removing identified duplicates, identifying (104) data values that lie above a predefined maximum threshold data value or identifying (105) data values that lie below a predefined minimum threshold data value and removing data associated to said identified data values, identifying (106) data values that differ from predetermined expected data values by more than a predetermined amount and removing data associated to said identified data values, identifying (107) incomplete data for which data values are missing and removing identified incomplete data, identifying (108) at least one predetermined time-dependent data pattern and removing data associated to said identified time-dependent data pattern, providing (109) the extracted second medical data set as input to a blood glucose level prediction model, and predicting (110) future blood glucose levels of the patient using the output of the blood glucose level prediction model based on the second medical data set.</description><subject>HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA</subject><subject>INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZHDwTS3JyE9RSMxLUchNTcwrVkjLL1IoyC8uKSgCimUm5igk5eQDFaTnlCbnF6cq5KSWpeYoFBSlpmQml2Tm5_EwsKYl5hSn8kJpbgY5N9cQZw_d1IL8-NTigsTk1LzUknhPH2MDMwMLS0djggoAtmwwSA</recordid><startdate>20231101</startdate><enddate>20231101</enddate><creator>REITERER Florian</creator><creator>ADELBERGER Daniel</creator><creator>SCHRANGL Patrick</creator><creator>RINGEMANN Christian</creator><creator>DEL RE Luigi</creator><scope>EVB</scope></search><sort><creationdate>20231101</creationdate><title>Method and means for postprandial blood glucose level prediction</title><author>REITERER Florian ; ADELBERGER Daniel ; SCHRANGL Patrick ; RINGEMANN Christian ; DEL RE Luigi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_IL306089A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng ; heb</language><creationdate>2023</creationdate><topic>HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA</topic><topic>INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>REITERER Florian</creatorcontrib><creatorcontrib>ADELBERGER Daniel</creatorcontrib><creatorcontrib>SCHRANGL Patrick</creatorcontrib><creatorcontrib>RINGEMANN Christian</creatorcontrib><creatorcontrib>DEL RE Luigi</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>REITERER Florian</au><au>ADELBERGER Daniel</au><au>SCHRANGL Patrick</au><au>RINGEMANN Christian</au><au>DEL RE Luigi</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Method and means for postprandial blood glucose level prediction</title><date>2023-11-01</date><risdate>2023</risdate><abstract>The invention relates to a method (100) for predicting blood glucose levels, in particular for postprandial blood glucose level prediction, the method being computer-implemented and comprising: receiving (101) a first medical data set of a patient covering a time range, said first medical data set comprising glucose data and further other medical data of said patient, extracting (102) a second medical data set from said first medical data set, wherein the second medical data set is a subset of the first medical data set and wherein the extracting comprises at least one of: identifying (103) duplicates in the first medical data set and removing identified duplicates, identifying (104) data values that lie above a predefined maximum threshold data value or identifying (105) data values that lie below a predefined minimum threshold data value and removing data associated to said identified data values, identifying (106) data values that differ from predetermined expected data values by more than a predetermined amount and removing data associated to said identified data values, identifying (107) incomplete data for which data values are missing and removing identified incomplete data, identifying (108) at least one predetermined time-dependent data pattern and removing data associated to said identified time-dependent data pattern, providing (109) the extracted second medical data set as input to a blood glucose level prediction model, and predicting (110) future blood glucose levels of the patient using the output of the blood glucose level prediction model based on the second medical data set.</abstract><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier
ispartof
issn
language eng ; heb
recordid cdi_epo_espacenet_IL306089A
source esp@cenet
subjects 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 Method and means for postprandial blood glucose level prediction
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-28T19%3A25%3A56IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=REITERER%20Florian&rft.date=2023-11-01&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EIL306089A%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true