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Sökning: WFRF:(Gustafsson Claes) > VAI-B: A multicente...

LIBRIS Formathandbok  (Information om MARC21)
FältnamnIndikatorerMetadata
00006949naa a2200637 4500
001oai:DiVA.org:kth-342632
003SwePub
008240125s2023 | |||||||||||000 ||eng|
009oai:lup.lub.lu.se:27fa0d57-b3ef-4651-a3be-4fb48cfb35ed
009oai:prod.swepub.kib.ki.se:236949901
0247 a https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3426322 URI
0247 a https://doi.org/10.1117/1.JMI.10.6.0614042 DOI
0247 a https://lup.lub.lu.se/record/27fa0d57-b3ef-4651-a3be-4fb48cfb35ed2 URI
0247 a http://kipublications.ki.se/Default.aspx?queryparsed=id:2369499012 URI
040 a (SwePub)kthd (SwePub)lud (SwePub)ki
041 a engb eng
042 9 SwePub
072 7a ref2 swepub-contenttype
072 7a art2 swepub-publicationtype
1001 a Cossío, Fernandou Karolinska Institutet,Karolinska Institute,Karolinska Institute Department of Oncology-Pathology Stockholm Sweden; Karolinska University Hospital Department of Radiology Stockholm Sweden4 aut
2451 0a VAI-B: A multicenter platform for the external validation of artificial intelligence algorithms in breast imaging
264 1b SPIE-Intl Soc Optical Eng,c 2023
338 a print2 rdacarrier
500 a QC 20240301
520 a Purpose: Multiple vendors are currently offering artificial intelligence (AI) computer-aided systems for triage detection, diagnosis, and risk prediction of breast cancer based on screening mammography. There is an imminent need to establish validation platforms that enable fair and transparent testing of these systems against external data. Approach: We developed validation of artificial intelligence for breast imaging (VAI-B), a platform for independent validation of AI algorithms in breast imaging. The platform is a hybrid solution, with one part implemented in the cloud and another in an on-premises environment at Karolinska Institute. Cloud services provide the flexibility of scaling the computing power during inference time, while secure on-premises clinical data storage preserves their privacy. A MongoDB database and a python package were developed to store and manage the data onpremises. VAI-B requires four data components: radiological images, AI inferences, radiologist assessments, and cancer outcomes. Results: To pilot test VAI-B, we defined a case-control population based on 8080 patients diagnosed with breast cancer and 36,339 healthy women based on the Swedish national quality registry for breast cancer. Images and radiological assessments from more than 100,000 mammography examinations were extracted from hospitals in three regions of Sweden. The images were processed by AI systems from three vendors in a virtual private cloud to produce abnormality scores related to signs of cancer in the images. A total of 105,706 examinations have been processed and stored in the database. Conclusions: We have created a platform that will allow downstream evaluation of AI systems for breast cancer detection, which enables faster development cycles for participating vendors and safer AI adoption for participating hospitals. The platform was designed to be scalable and ready to be expanded should a new vendor want to evaluate their system or should a new hospital wish to obtain an evaluation of different AI systems on their images.
650 7a MEDICIN OCH HÄLSOVETENSKAPx Klinisk medicinx Radiologi och bildbehandling0 (SwePub)302082 hsv//swe
650 7a MEDICAL AND HEALTH SCIENCESx Clinical Medicinex Radiology, Nuclear Medicine and Medical Imaging0 (SwePub)302082 hsv//eng
650 7a MEDICIN OCH HÄLSOVETENSKAPx Klinisk medicinx Cancer och onkologi0 (SwePub)302032 hsv//swe
650 7a MEDICAL AND HEALTH SCIENCESx Clinical Medicinex Cancer and Oncology0 (SwePub)302032 hsv//eng
653 a breast cancer
653 a data management
653 a machine learning
653 a mammography
653 a validation
653 a breast cancer
653 a data management
653 a machine learning
653 a mammography
653 a validation
7001 a Schurz, Haikou Karolinska Institutet,Karolinska Institute,Karolinska Institute Department of Oncology-Pathology Stockholm Sweden4 aut
7001 a Engström, Mathiasu Collective Minds Radiology Stockholm Sweden4 aut
7001 a Barck-Holst, Carlu West Code Group Stockholm Sweden4 aut
7001 a Tsirikoglou, Apostoliau Karolinska Institutet,Karolinska Institute,Karolinska Institute Department of Oncology-Pathology Stockholm Sweden4 aut
7001 a Lundström, Claesu Linköping University,Linköping University Center for Medical Image Science and Visualization (CMIV) Linköping Sweden4 aut
7001 a Gustafsson, Håkanu Linköping University,Linköping University Center for Medical Image Science and Visualization (CMIV) Linköping Sweden; Linköping University Department of Medical Radiation Physics Department of Health Medicine and Caring Sciences Linköping Sweden4 aut
7001 a Smith, Kevin,d 1975-u KTH Royal Institute of Technology,KTH,Beräkningsvetenskap och beräkningsteknik (CST)4 aut0 (Swepub:kth)u1l33jpf
7001 a Zackrisson, Sophiau Lund University,Lunds universitet,Diagnostisk radiologi, Malmö,Forskargrupper vid Lunds universitet,LUCC: Lunds universitets cancercentrum,Övriga starka forskningsmiljöer,LTH profilområde: Avancerade ljuskällor,LTH profilområden,Lunds Tekniska Högskola,LU profilområde: Ljus och material,Lunds universitets profilområden,Radiology Diagnostics, Malmö,Lund University Research Groups,LUCC: Lund University Cancer Centre,Other Strong Research Environments,LTH Profile Area: Photon Science and Technology,LTH Profile areas,Faculty of Engineering, LTH,LU Profile Area: Light and Materials,Lund University Profile areas,Lund University Department of Diagnostic Radiology Translational Medicine Malmö Sweden; Skåne University Hospital Department of Imaging and Physiology Malmö Sweden4 aut0 (Swepub:lu)smi-sza
7001 a Strand, Fredriku Karolinska Institutet,Karolinska Institute,Karolinska Institute Department of Oncology-Pathology Stockholm Sweden; Karolinska University Hospital Department of Radiology Stockholm Sweden4 aut
7102 a Karolinska Instituteb Karolinska Institute Department of Oncology-Pathology Stockholm Sweden; Karolinska University Hospital Department of Radiology Stockholm Sweden4 org
7730 t Journal of Medical Imagingd : SPIE-Intl Soc Optical Engg 10:6q 10:6x 2329-4302x 2329-4310
8564 u https://doi.org/10.1117/1.JMI.10.6.061404y Fulltext
8564 u http://dx.doi.org/10.1117/1.JMI.10.6.061404x freey FULLTEXT
8564 8u https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-342632
8564 8u https://doi.org/10.1117/1.JMI.10.6.061404
8564 8u https://lup.lub.lu.se/record/27fa0d57-b3ef-4651-a3be-4fb48cfb35ed
8564 8u http://kipublications.ki.se/Default.aspx?queryparsed=id:236949901

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