Utvärdering av marknad och analysmetoder för snabbtest av antibiotikaresistens för polymikrobiella blodprover : En studie för utveckling av icke-invasiva optiska metoder och automatisering med maskininlärning

Gradientech AB is a company that develops a new ultra-rapid system for antibiotic susceptibility testing and their product will hopefully be used in health care for more efficient diagnosis of sepsis. Today the product has difficulties with the analysis of polymicrobial tests. For our project, the t...

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Main Authors: Jansson, Linnéa, Johnson, Gustav, Wallskog, Amanda, Svalberg, Linn, Svärd, Karl, Engström Kindmark, Hedvig, Dost, Maryam
Format: Others
Language:Swedish
Published: Uppsala universitet, Institutionen för biologisk grundutbildning 2019
Subjects:
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-384703
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spelling ndltd-UPSALLA1-oai-DiVA.org-uu-3847032019-06-12T04:29:19ZUtvärdering av marknad och analysmetoder för snabbtest av antibiotikaresistens för polymikrobiella blodprover : En studie för utveckling av icke-invasiva optiska metoder och automatisering med maskininlärningsweJansson, LinnéaJohnson, GustavWallskog, AmandaSvalberg, LinnSvärd, KarlEngström Kindmark, HedvigDost, MaryamUppsala universitet, Institutionen för biologisk grundutbildningUppsala universitet, Institutionen för biologisk grundutbildningUppsala universitet, Institutionen för biologisk grundutbildningUppsala universitet, Institutionen för biologisk grundutbildningUppsala universitet, Institutionen för biologisk grundutbildningUppsala universitet, Institutionen för biologisk grundutbildning2019antibiotikaresistensmaskininlärningoptiska metoderantibiotikamarknadsundersökningsepsisdiagnostiksnabbtest av MIC-värdebildanalyssjukvårdNatural SciencesNaturvetenskapGradientech AB is a company that develops a new ultra-rapid system for antibiotic susceptibility testing and their product will hopefully be used in health care for more efficient diagnosis of sepsis. Today the product has difficulties with the analysis of polymicrobial tests. For our project, the task is therefore to examine the market and the demand for the ability to detect polymicrobial infections. Our project is meant to provide ideas for improvements on their current method for the feasibility to detect several types of bacteria in the same test. Through literature studies, we have received an overview of how optical methods using image analysis can work and how they could be implemented in Gradientech's product. Image analysis can make the identification of bacteria possible. Interesting objects in the image can be distinguished from each other with filters that handle, for example, size, shape and light intensity. A potential improvement in the classification of bacteria by optical methods may be to test several different angles and wavelengths. This is to get more training data for machine learning and thus more accurately detect and analyze samples. The results from literature studies and interviews with clinicians, a microbiologist, and professor in image analysis have led to a conclusion that techniques that contribute to a decrease of antimicrobial resistance will be crucial for the future. In Sweden, the development of resistant bacteria is pretty low, but in many other parts of the world, there is a different reality. The product’s greatest potential will probably be in countries with a high incidence of resistant bacteria and with educated personnel available to use the product. Ultra-rapid systems for AST can contribute to saving lives by making sure that the right type of antibiotics is given directly. Detection and identification of polymicrobial samples in sepsis are also relevant, but it will not contribute to reduced antibiotic use since the patient's health will always be prioritized as of now. Finally, we reached the conclusion that identification of polymicrobial tests is not a necessary feature for the success of the product. This is above all due to the mass spectrometry method MALDI-TOF, a technique that is already well-established in health care systems. It can quickly and cheaply identify bacteria in clinical samples. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-384703application/pdfinfo:eu-repo/semantics/openAccess
collection NDLTD
language Swedish
format Others
sources NDLTD
topic antibiotikaresistens
maskininlärning
optiska metoder
antibiotika
marknadsundersökning
sepsis
diagnostik
snabbtest av MIC-värde
bildanalys
sjukvård
Natural Sciences
Naturvetenskap
spellingShingle antibiotikaresistens
maskininlärning
optiska metoder
antibiotika
marknadsundersökning
sepsis
diagnostik
snabbtest av MIC-värde
bildanalys
sjukvård
Natural Sciences
Naturvetenskap
Jansson, Linnéa
Johnson, Gustav
Wallskog, Amanda
Svalberg, Linn
Svärd, Karl
Engström Kindmark, Hedvig
Dost, Maryam
Utvärdering av marknad och analysmetoder för snabbtest av antibiotikaresistens för polymikrobiella blodprover : En studie för utveckling av icke-invasiva optiska metoder och automatisering med maskininlärning
description Gradientech AB is a company that develops a new ultra-rapid system for antibiotic susceptibility testing and their product will hopefully be used in health care for more efficient diagnosis of sepsis. Today the product has difficulties with the analysis of polymicrobial tests. For our project, the task is therefore to examine the market and the demand for the ability to detect polymicrobial infections. Our project is meant to provide ideas for improvements on their current method for the feasibility to detect several types of bacteria in the same test. Through literature studies, we have received an overview of how optical methods using image analysis can work and how they could be implemented in Gradientech's product. Image analysis can make the identification of bacteria possible. Interesting objects in the image can be distinguished from each other with filters that handle, for example, size, shape and light intensity. A potential improvement in the classification of bacteria by optical methods may be to test several different angles and wavelengths. This is to get more training data for machine learning and thus more accurately detect and analyze samples. The results from literature studies and interviews with clinicians, a microbiologist, and professor in image analysis have led to a conclusion that techniques that contribute to a decrease of antimicrobial resistance will be crucial for the future. In Sweden, the development of resistant bacteria is pretty low, but in many other parts of the world, there is a different reality. The product’s greatest potential will probably be in countries with a high incidence of resistant bacteria and with educated personnel available to use the product. Ultra-rapid systems for AST can contribute to saving lives by making sure that the right type of antibiotics is given directly. Detection and identification of polymicrobial samples in sepsis are also relevant, but it will not contribute to reduced antibiotic use since the patient's health will always be prioritized as of now. Finally, we reached the conclusion that identification of polymicrobial tests is not a necessary feature for the success of the product. This is above all due to the mass spectrometry method MALDI-TOF, a technique that is already well-established in health care systems. It can quickly and cheaply identify bacteria in clinical samples.
author Jansson, Linnéa
Johnson, Gustav
Wallskog, Amanda
Svalberg, Linn
Svärd, Karl
Engström Kindmark, Hedvig
Dost, Maryam
author_facet Jansson, Linnéa
Johnson, Gustav
Wallskog, Amanda
Svalberg, Linn
Svärd, Karl
Engström Kindmark, Hedvig
Dost, Maryam
author_sort Jansson, Linnéa
title Utvärdering av marknad och analysmetoder för snabbtest av antibiotikaresistens för polymikrobiella blodprover : En studie för utveckling av icke-invasiva optiska metoder och automatisering med maskininlärning
title_short Utvärdering av marknad och analysmetoder för snabbtest av antibiotikaresistens för polymikrobiella blodprover : En studie för utveckling av icke-invasiva optiska metoder och automatisering med maskininlärning
title_full Utvärdering av marknad och analysmetoder för snabbtest av antibiotikaresistens för polymikrobiella blodprover : En studie för utveckling av icke-invasiva optiska metoder och automatisering med maskininlärning
title_fullStr Utvärdering av marknad och analysmetoder för snabbtest av antibiotikaresistens för polymikrobiella blodprover : En studie för utveckling av icke-invasiva optiska metoder och automatisering med maskininlärning
title_full_unstemmed Utvärdering av marknad och analysmetoder för snabbtest av antibiotikaresistens för polymikrobiella blodprover : En studie för utveckling av icke-invasiva optiska metoder och automatisering med maskininlärning
title_sort utvärdering av marknad och analysmetoder för snabbtest av antibiotikaresistens för polymikrobiella blodprover : en studie för utveckling av icke-invasiva optiska metoder och automatisering med maskininlärning
publisher Uppsala universitet, Institutionen för biologisk grundutbildning
publishDate 2019
url http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-384703
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