Ibex Selected by Kantonsspital Baselland to Deliver the First AI-powered Cancer Diagnostics Solution in Switzerland
Kantonsspital Baselland to deploy the AI-powered Galen™ platform, helping pathologists improve accuracy and efficiency during primary cancer diagnosis
TEL AVIV, Israel and BASEL, Switzerland, Nov. 3, 2021 /PRNewswire/ -- Ibex Medical Analytics, the pioneer in artificial intelligence (AI) -powered cancer diagnostics and Kantonsspital Baselland, a healthcare provider in Northwestern Switzerland, today announced the first deployment in Switzerland of an AI solution supporting pathologists during routine cancer diagnosis.
Pathologists play a crucial role in the detection and diagnosis of disease, with their assessments being vital for reaching correct treatment decisions by oncologists. However, a rise in cancer prevalence and advances in personalized medicine have resulted in growing diagnostic complexity, which significantly increases pathologists' workloads. As pathology labs transition towards digital solutions, pathologists can implement AI-enhanced workflows to improve quality and efficiency of cancer diagnosis, resulting in better patient care.
Ibex transforms cancer diagnosis by harnessing AI and machine learning technology at an unprecedented scale. Ibex's Galen platform helps pathologists improve the quality of cancer diagnosis, reduce diagnosis time, boost productivity1, and implement real-time quality control2. It is CE marked for breast and prostate cancer detection in multiple workflows and was recently granted Breakthrough Device Designation by the U.S. Food and Drug Administration (FDA). Galen has already demonstrated outstanding outcomes in clinical studies3,4 and deployed in labs worldwide where it is used as part of everyday clinical practice.
Kantonsspital Baselland (KSBL) is a hospital providing histological and molecular integrative cancer diagnostics and personalized care for tumor patients. KSBL have digitized their pathology services using Philips' IntelliSite Pathology Solution, deploying a network of high-throughout digital pathology scanners, as well as an image management solution and an internally developed lab information system. As part of the AI deployment, pathologists at KSBL will use the Galen platform, enabling them to streamline workflows and improve accuracy during primary diagnosis via automated case prioritization, cancer heatmaps, grading and other productivity-enhancing tools.
"Timely diagnosis delivered with the utmost quality are a cornerstone of cancer care at Kantonsspital Bselland, and we are committed to continually improving the technology and processes in our lab," said Kirsten Mertz MD, Professor of Pathology at KSBL. "We were among the pioneers in adopting digital pathology in Switzerland and take special pride in being the first hospital in the country to implement artificial intelligence in pathology. We were impressed with the performance demonstrated by Ibex's AI technology across multiple clinical studies in Europe and the United States and look forward to getting hands on experience in working with their solution and examining how it can help improve patient care."
"We are thrilled to team up with Kantonsspital Baselland and enable their pathologists to use state-of-the-art AI-powered solutions to more accurately detect cancer and improve quality and efficiency of diagnosis," said Stuart Shand, Chief Commercial Officer at Ibex Medical Analytics. "With this cooperation, KSBL sets a new standard in cancer care quality, further proving its leadership and commitment to its patients by deploying an advanced clinical-grade AI solution to ensure the best possible outcomes. artificial intelligence and digital pathology technologies become an essential part of cancer care programs, their adoption being a vision shared by both KSBL and Ibex."
About Kantonsspital Baselland
The Kantonsspital Baselland (KSBL) is a hospital in Northwestern Switzerland with 3,300 employees that provides care for several thousand tumor patients each year. Among those approximately 150 patients are newly diagnosed with prostate cancer each year. The Cantonal Institute of Pathology is the pathology department of KSBL and provides high-end histological and molecular cancer diagnostic service.
About Ibex Medical Analytics
Ibex pioneers AI-powered cancer diagnostics in pathology. We empower physicians to provide every patient with an accurate, timely and personalized cancer diagnosis by developing clinical-grade AI algorithms and digital workflows that help detect and grade cancer in biopsies. Our Galen™ platform is the first-ever AI-powered integrated diagnostics solution in pathology and used in routine clinical practice worldwide, supporting pathologists and providers in improving the quality and accuracy of diagnosis, implementing comprehensive quality control, reducing turnaround times and boosting productivity with more efficient workflows. Ibex's Artificial Intelligence technology is built on Deep Learning algorithms trained by a team of pathologists, data scientists and software engineers. For more information, go to www.ibex-ai.com.
Media Contacts
Yael Hart
GK for Ibex
yael@gkpr.com
[1] Raoux D et al, Novel AI Based Solution for Supporting Primary Diagnosis of Prostate Cancer Increases the Accuracy and Efficiency of Reporting in Clinical Routine. USCAP 2021: https://www.youtube.com/watch?v=9XuWK8PmUlw
[2] Sandbank J et al, Deployment of a Multi-Tissue AI-based Quality Control System in Routine Clinical Workflow. European Conference of Pathology 2020: https://ibex-ai.com/wp-content/uploads/2021/03/Maccabi-IBEX-ECP2020-poster.pdf
[3] The LANCET Digital Health, Aug 2020, Pantanowitz et al, An artificial intelligence algorithm for prostate cancer diagnosis in whole slide images of core needle biopsies: a blinded clinical validation and deployment study https://www.thelancet.com/journals/landig/article/PIIS2589-7500(20)30159-X/fulltext
[4] Laifenfeld D et al, AI-Based Solution for Cancer Diagnosis in Prostate Core Needle Biopsies: A Prospective Blinded Multi-Site Clinical Study. USCAP 2021: https://www.youtube.com/watch?v=9nDiJY90v9c
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