POLAR (Q3988817): Difference between revisions
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Colon cancer is the third most common type of cancer in the Netherlands. Colon cancer is caused by the development of polyps to colon cancer. In order to detect colon cancer and pre-stages in a timely manner, the nationwide population cancer study was introduced in 2014 on the basis of a stool test. All people with a positive stool test are advised to undergo a coloscopy to view, remove and pathologically analyse polyps. The introduction of the population survey has resulted in an annual increase in the number of coloscopies, and this will only increase as a result of ageing. This results in long waiting lists and increasing costs. Currently, all polyps are being sent in for pathological research. About 80 to 90 % of all these polyps are small polyps with a minimal risk of colon cancer. Due to the high prevalence of small polyps with at that time minimal risk of colon cancer, the “optical diagnosis strategy” has been developed. When using the “optical diagnosis strategy”, small polyps in the colon are assessed by the high or low-security endoscopist. With high certainty, this strategy removes the small polyp and throws it away without the assessment of the pathologist. At the same time, small hyperplastic polyps are left in situ because they are considered innocent. However, if an endoscopist can make an optical diagnosis based on the appearance of the polyp only with low reliability, the polyp is sent to the pathologist. The optical diagnosis strategy leads to a significant reduction in the time and costs associated with coloscopy. In addition, the innovation contributes to reducing the risk of complications, as not every polyp has to be removed anymoreRecent studies show that the diagnostic accuracy of this “optical diagnosis strategy” is highly dependent on the training and experience of the endoscopist. In order to increase the accuracy of optical diagnosis, recent research on computer-aided diagnosis (CAD) has been carried out. Artificially intelligent programs can be developed that help endoscopists in the accurate classification of polyps. Despite the fact that artificial intelligence has shown potential as a diagnostic tool in recently published international studies, this technology is not yet being applied in an operational environment. In the light of the above, the project partners want to develop a classification tool, called POLAR, for polyps. Through the use of convolutional neural networks, the project partners intend to incorporate the golden standard of pathological analysis into a system in order to make a significant contribution to the reliability of the “optical diagnosis strategy” and the sustainability of Dutch care. The project contributes to an increase in valorisation and innovation within ZiuZ and relevant SMEs. The collaboration between ZiuZ, AMC/AMR, the MCL and the Society is a good example of a crossover between the ‘life science’ and ‘high-tech’ sector. The project also fits seamlessly with the societal challenge ‘health, demography and well-being’. With this project, project partners intend to push the boundaries of artificial intelligence applications in the healthcare sector. The techniques used by ZiuZ in the development of the classification tool, such as convolutional neural networks, are highly innovative techniques and constitute the current spearheads of artificial intelligence research. Especially in the medical world, these techniques are still very limited. Innovative is also the development of a tool that can classify polyps on a macroscopic level. Project partners expect to have a major impact on the reduction of healthcare costs in the Netherlands, Europe and the United States. First numerical analyses show that POLAR leads to savings in the tens of millions. In addition, the demand for artificial intelligence in healthcare is increasing according to research firm Gartner. With a new earning model, ZiuZ expects hospitals to board easily. From detailed calculations it is considered plausible that POLAR can achieve a turnover of EUR 6.1 million in 2025 and an increase in staff of 18.7 FTE. These are high-quality jobs.The most important aspect of sustainability is that there is an optimisation of the classification of polyps. This makes a significant contribution to keeping care affordable. In addition, the risk of complications decreases. It also leads to a much faster diagnosis for a group of patients, which reduces stress. The investigation will be carried out in accordance with the General Data Protection Regulation. (English) | |||||||||||||||
| Property / summary: Colon cancer is the third most common type of cancer in the Netherlands. Colon cancer is caused by the development of polyps to colon cancer. In order to detect colon cancer and pre-stages in a timely manner, the nationwide population cancer study was introduced in 2014 on the basis of a stool test. All people with a positive stool test are advised to undergo a coloscopy to view, remove and pathologically analyse polyps. The introduction of the population survey has resulted in an annual increase in the number of coloscopies, and this will only increase as a result of ageing. This results in long waiting lists and increasing costs. Currently, all polyps are being sent in for pathological research. About 80 to 90 % of all these polyps are small polyps with a minimal risk of colon cancer. Due to the high prevalence of small polyps with at that time minimal risk of colon cancer, the “optical diagnosis strategy” has been developed. When using the “optical diagnosis strategy”, small polyps in the colon are assessed by the high or low-security endoscopist. With high certainty, this strategy removes the small polyp and throws it away without the assessment of the pathologist. At the same time, small hyperplastic polyps are left in situ because they are considered innocent. However, if an endoscopist can make an optical diagnosis based on the appearance of the polyp only with low reliability, the polyp is sent to the pathologist. The optical diagnosis strategy leads to a significant reduction in the time and costs associated with coloscopy. In addition, the innovation contributes to reducing the risk of complications, as not every polyp has to be removed anymoreRecent studies show that the diagnostic accuracy of this “optical diagnosis strategy” is highly dependent on the training and experience of the endoscopist. In order to increase the accuracy of optical diagnosis, recent research on computer-aided diagnosis (CAD) has been carried out. Artificially intelligent programs can be developed that help endoscopists in the accurate classification of polyps. Despite the fact that artificial intelligence has shown potential as a diagnostic tool in recently published international studies, this technology is not yet being applied in an operational environment. In the light of the above, the project partners want to develop a classification tool, called POLAR, for polyps. Through the use of convolutional neural networks, the project partners intend to incorporate the golden standard of pathological analysis into a system in order to make a significant contribution to the reliability of the “optical diagnosis strategy” and the sustainability of Dutch care. The project contributes to an increase in valorisation and innovation within ZiuZ and relevant SMEs. The collaboration between ZiuZ, AMC/AMR, the MCL and the Society is a good example of a crossover between the ‘life science’ and ‘high-tech’ sector. The project also fits seamlessly with the societal challenge ‘health, demography and well-being’. With this project, project partners intend to push the boundaries of artificial intelligence applications in the healthcare sector. The techniques used by ZiuZ in the development of the classification tool, such as convolutional neural networks, are highly innovative techniques and constitute the current spearheads of artificial intelligence research. Especially in the medical world, these techniques are still very limited. Innovative is also the development of a tool that can classify polyps on a macroscopic level. Project partners expect to have a major impact on the reduction of healthcare costs in the Netherlands, Europe and the United States. First numerical analyses show that POLAR leads to savings in the tens of millions. In addition, the demand for artificial intelligence in healthcare is increasing according to research firm Gartner. With a new earning model, ZiuZ expects hospitals to board easily. From detailed calculations it is considered plausible that POLAR can achieve a turnover of EUR 6.1 million in 2025 and an increase in staff of 18.7 FTE. These are high-quality jobs.The most important aspect of sustainability is that there is an optimisation of the classification of polyps. This makes a significant contribution to keeping care affordable. In addition, the risk of complications decreases. It also leads to a much faster diagnosis for a group of patients, which reduces stress. The investigation will be carried out in accordance with the General Data Protection Regulation. (English) / rank | |||||||||||||||
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| Property / summary: Colon cancer is the third most common type of cancer in the Netherlands. Colon cancer is caused by the development of polyps to colon cancer. In order to detect colon cancer and pre-stages in a timely manner, the nationwide population cancer study was introduced in 2014 on the basis of a stool test. All people with a positive stool test are advised to undergo a coloscopy to view, remove and pathologically analyse polyps. The introduction of the population survey has resulted in an annual increase in the number of coloscopies, and this will only increase as a result of ageing. This results in long waiting lists and increasing costs. Currently, all polyps are being sent in for pathological research. About 80 to 90 % of all these polyps are small polyps with a minimal risk of colon cancer. Due to the high prevalence of small polyps with at that time minimal risk of colon cancer, the “optical diagnosis strategy” has been developed. When using the “optical diagnosis strategy”, small polyps in the colon are assessed by the high or low-security endoscopist. With high certainty, this strategy removes the small polyp and throws it away without the assessment of the pathologist. At the same time, small hyperplastic polyps are left in situ because they are considered innocent. However, if an endoscopist can make an optical diagnosis based on the appearance of the polyp only with low reliability, the polyp is sent to the pathologist. The optical diagnosis strategy leads to a significant reduction in the time and costs associated with coloscopy. In addition, the innovation contributes to reducing the risk of complications, as not every polyp has to be removed anymoreRecent studies show that the diagnostic accuracy of this “optical diagnosis strategy” is highly dependent on the training and experience of the endoscopist. In order to increase the accuracy of optical diagnosis, recent research on computer-aided diagnosis (CAD) has been carried out. Artificially intelligent programs can be developed that help endoscopists in the accurate classification of polyps. Despite the fact that artificial intelligence has shown potential as a diagnostic tool in recently published international studies, this technology is not yet being applied in an operational environment. In the light of the above, the project partners want to develop a classification tool, called POLAR, for polyps. Through the use of convolutional neural networks, the project partners intend to incorporate the golden standard of pathological analysis into a system in order to make a significant contribution to the reliability of the “optical diagnosis strategy” and the sustainability of Dutch care. The project contributes to an increase in valorisation and innovation within ZiuZ and relevant SMEs. The collaboration between ZiuZ, AMC/AMR, the MCL and the Society is a good example of a crossover between the ‘life science’ and ‘high-tech’ sector. The project also fits seamlessly with the societal challenge ‘health, demography and well-being’. With this project, project partners intend to push the boundaries of artificial intelligence applications in the healthcare sector. The techniques used by ZiuZ in the development of the classification tool, such as convolutional neural networks, are highly innovative techniques and constitute the current spearheads of artificial intelligence research. Especially in the medical world, these techniques are still very limited. Innovative is also the development of a tool that can classify polyps on a macroscopic level. Project partners expect to have a major impact on the reduction of healthcare costs in the Netherlands, Europe and the United States. First numerical analyses show that POLAR leads to savings in the tens of millions. In addition, the demand for artificial intelligence in healthcare is increasing according to research firm Gartner. With a new earning model, ZiuZ expects hospitals to board easily. From detailed calculations it is considered plausible that POLAR can achieve a turnover of EUR 6.1 million in 2025 and an increase in staff of 18.7 FTE. These are high-quality jobs.The most important aspect of sustainability is that there is an optimisation of the classification of polyps. This makes a significant contribution to keeping care affordable. In addition, the risk of complications decreases. It also leads to a much faster diagnosis for a group of patients, which reduces stress. The investigation will be carried out in accordance with the General Data Protection Regulation. (English) / qualifier | |||||||||||||||
point in time: 15 December 2021
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Revision as of 06:19, 15 December 2021
Project Q3988817 in Netherlands
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | POLAR |
Project Q3988817 in Netherlands |
Statements
1,521,482.21 Euro
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4,019,768.058 Euro
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37.85 percent
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1 May 2018
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29 October 2021
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Academisch Medisch Centrum
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52°17'38.94"N, 4°57'28.19"E
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53°11'22.88"N, 5°48'15.08"E
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53°3'27.18"N, 6°15'22.97"E
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53°0'22.61"N, 6°3'48.71"E
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1100 DD
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1105 AZ
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9243 WG
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8901 BR
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8934 AD
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8400 AC
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8401 DK
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8400 AC
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8400 AC
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Dikke darmkanker is de derde meest voorkomende vorm van kanker in Nederland. Darmkanker ontstaat door ontwikkeling van poliepen tot darmkanker. Om darmkanker en voorstadia tijdig te detecteren, is in 2014 het landelijk bevolkingsonderzoek darmkanker ingevoerd op basis van een ontlastingstest. Alle mensen met een positieve ontlastingstest wordt geadviseerd een coloscopie te ondergaan om poliepen te bekijken, te verwijderen en pathologisch te analyseren. De invoering van het bevolkingsonderzoek heeft geresulteerd in een jaarlijkse toename van het aantal coloscopieën en door vergrijzing zal dit alleen maar meer toenemen. Dit resulteert in lange wachtlijsten en toenemende kosten. Momenteel worden alle poliepen ingezonden voor pathologisch onderzoek. Ongeveer 80 tot 90% van al deze ingezonden poliepen zijn kleine poliepen met een miniem risico op darmkanker. Vanwege de hoge prevalentie van kleine poliepen met op dat moment minimaal risico op darmkanker is de “optische diagnose strategie” ontwikkeld. Bij gebruik van de “optische diagnose strategie” worden kleine poliepen in de dikke darm door de endoscopist met een hoge of lage zekerheid beoordeeld. Bij hoge zekerheid wordt bij deze strategie de kleine poliep verwijderd en weggegooid zonder beoordeling van de patholoog. Tevens worden met hoge zekerheid beoordeelde kleine hyperplastische poliepen in situ gelaten, omdat deze als onschuldig worden beschouwd. Als een endoscopist echter op basis van het uiterlijk van de poliep alleen met een lage betrouwbaarheid een optische diagnose kan stellen, dan wordt de poliep opgestuurd naar de patholoog. De optische diagnose strategie leidt tot een significante reductie van de tijd en kosten die gepaard gaan met coloscopieën. Daarnaast levert de innovatie een bijdrage aan het reduceren van de kans op complicaties, omdat niet elke poliep meer hoeft te worden verwijderdRecente studies laten echter zien dat de diagnostische accuratesse van deze “optische diagnose strategie” sterk afhankelijk is van de training en ervaring van de endoscopist. Om de accuratesse van de optische diagnose te vergroten is recent onderzoek gedaan naar “computer-aided diagnosis” (CAD). Door middel van artificiële intelligente kunnen programma’s worden ontwikkeld die endoscopisten helpen bij de accurate classificatie van poliepen. Ondanks dat artificiële intelligentie in recent gepubliceerde internationale studies heeft laten zien potentie te hebben als diagnostisch hulpmiddel, wordt deze technologie nog niet toegepast in een operationele omgeving. De projectpartners willen in het licht van bovenstaande een classificatietool, genaamd POLAR, voor poliepen ontwikkelen. Door middel van het toepassen van convolutionele neurale netwerken zijn de projectpartners voornemens de gouden standaard van de pathologische analyse in een systeem te vatten en zo een significante bijdrage te kunnen leveren aan de betrouwbaarheid van de “optische diagnose strategie” en het betaalbaar houden van de Nederlandse zorg. Het project draagt bij aan een toename van valorisatie en innovatie binnen ZiuZ en betrokken MKB-ers. De samenwerking tussen ZiuZ, het AMC/AMR, het MCL en de Maatschap is een goed voorbeeld van een cross-over tussen de ‘life science’ en ‘hightech’ sector. Tevens sluit het project naadloos aan bij de maatschappelijke uitdaging ‘gezondheid, demografie en welzijn’.Met dit project zijn projectpartners voornemens de grenzen van artificiële intelligentie toepassingen in de zorgsector te verleggen. De technieken die door ZiuZ worden toegepast in de ontwikkeling van de classificatietool, zoals convolutionele neurale netwerken, zijn zeer innovatieve technieken en vormen de huidige speerpunten van artificiële intelligentie onderzoek. Zeker in de medische wereld worden deze technieken nog erg beperkt ingezet. Innovatief is ook de ontwikkeling van een tool die poliepen op macroscopisch niveau kan classificeren. Projectpartners verwachten een grote impact te hebben op de reductie van de zorgkosten in Nederland, Europa en de Verenigde Staten. Eerste cijfermatige analyses laten zien dat POLAR leidt tot besparingen in de tientallen miljoenen. Daarnaast neemt de vraag naar kunstmatige intelligentie in de zorg volgens onderzoeksbureau Gartner toe. Met een nieuw verdienmodel verwacht ZiuZ dat ziekenhuizen makkelijk instappen. Uit gedetailleerde berekeningen wordt het aannemelijk geacht dat in 2025 met POLAR een omzet kan worden behaald van € 6,1 miljoen en een personeelsgroei van 18,7 FTE. Dit betreffen hoogwaardige banen.Het belangrijkste aspect van duurzaamheid is dat er een optimalisatie van de classificatie van poliepen plaatsvindt. Hierdoor wordt een significante bijdrage geleverd aan het betaalbaar houden van de zorg. Daarnaast neemt het risico op complicaties bij af. Tevens leidt het voor een groep patiënten tot een veel snellere diagnose, hetgeen stress vermindert. Het onderzoek zal conform de Algemene Verordening Gegevensbescherming worden uitgevoerd. (Dutch)
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Colon cancer is the third most common type of cancer in the Netherlands. Colon cancer is caused by the development of polyps to colon cancer. In order to detect colon cancer and pre-stages in a timely manner, the nationwide population cancer study was introduced in 2014 on the basis of a stool test. All people with a positive stool test are advised to undergo a coloscopy to view, remove and pathologically analyse polyps. The introduction of the population survey has resulted in an annual increase in the number of coloscopies, and this will only increase as a result of ageing. This results in long waiting lists and increasing costs. Currently, all polyps are being sent in for pathological research. About 80 to 90 % of all these polyps are small polyps with a minimal risk of colon cancer. Due to the high prevalence of small polyps with at that time minimal risk of colon cancer, the “optical diagnosis strategy” has been developed. When using the “optical diagnosis strategy”, small polyps in the colon are assessed by the high or low-security endoscopist. With high certainty, this strategy removes the small polyp and throws it away without the assessment of the pathologist. At the same time, small hyperplastic polyps are left in situ because they are considered innocent. However, if an endoscopist can make an optical diagnosis based on the appearance of the polyp only with low reliability, the polyp is sent to the pathologist. The optical diagnosis strategy leads to a significant reduction in the time and costs associated with coloscopy. In addition, the innovation contributes to reducing the risk of complications, as not every polyp has to be removed anymoreRecent studies show that the diagnostic accuracy of this “optical diagnosis strategy” is highly dependent on the training and experience of the endoscopist. In order to increase the accuracy of optical diagnosis, recent research on computer-aided diagnosis (CAD) has been carried out. Artificially intelligent programs can be developed that help endoscopists in the accurate classification of polyps. Despite the fact that artificial intelligence has shown potential as a diagnostic tool in recently published international studies, this technology is not yet being applied in an operational environment. In the light of the above, the project partners want to develop a classification tool, called POLAR, for polyps. Through the use of convolutional neural networks, the project partners intend to incorporate the golden standard of pathological analysis into a system in order to make a significant contribution to the reliability of the “optical diagnosis strategy” and the sustainability of Dutch care. The project contributes to an increase in valorisation and innovation within ZiuZ and relevant SMEs. The collaboration between ZiuZ, AMC/AMR, the MCL and the Society is a good example of a crossover between the ‘life science’ and ‘high-tech’ sector. The project also fits seamlessly with the societal challenge ‘health, demography and well-being’. With this project, project partners intend to push the boundaries of artificial intelligence applications in the healthcare sector. The techniques used by ZiuZ in the development of the classification tool, such as convolutional neural networks, are highly innovative techniques and constitute the current spearheads of artificial intelligence research. Especially in the medical world, these techniques are still very limited. Innovative is also the development of a tool that can classify polyps on a macroscopic level. Project partners expect to have a major impact on the reduction of healthcare costs in the Netherlands, Europe and the United States. First numerical analyses show that POLAR leads to savings in the tens of millions. In addition, the demand for artificial intelligence in healthcare is increasing according to research firm Gartner. With a new earning model, ZiuZ expects hospitals to board easily. From detailed calculations it is considered plausible that POLAR can achieve a turnover of EUR 6.1 million in 2025 and an increase in staff of 18.7 FTE. These are high-quality jobs.The most important aspect of sustainability is that there is an optimisation of the classification of polyps. This makes a significant contribution to keeping care affordable. In addition, the risk of complications decreases. It also leads to a much faster diagnosis for a group of patients, which reduces stress. The investigation will be carried out in accordance with the General Data Protection Regulation. (English)
15 December 2021
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Identifiers
OP-2014-2023-Noord-OPSNN0202
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