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...
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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 |
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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> |
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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 |
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