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CE-IVD marked the first time an AI solution for predictive risk stratification of breast cancer patients.

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Stratipath, the global leader in accurate AI-based diagnostic solutions, today announced that its AI program for predictive risk stratification of breast cancer, Stratipath Breast, is now CE-IVD marked.

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STOCKHOLM, Sweden, June 1, 2022 (GLOBE NEWSWIRE) – Stratipath, the global leader in accurate AI-based diagnostic solutions, today announced that its AI program for stratified diagnosis of breast cancer, Stratipath Breast, is now CE-IVD marked. This paves the way for clinical implementation in the European Union. Based on analysis of hematoxylin and eosin (H&E) full digital pathology slide images, the software provides new decision support for clinicians and enables precision medicine to more patients.

Stratipath Burst is the first EU regulatory compliant solution to classify breast cancer risk using accurate AI-based diagnostics to analyze cancerous tissues, enabling identification of patients with increased risk of disease progression.

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Unlike traditional molecular tests, AI-based risk profiling enables faster result times, provides new information at the point of diagnosis and reduces the need for expensive molecular tests, allowing for wider use and benefit for more patients.

Stratipath Breast provides a faster and cheaper alternative to molecular assays, allowing more patients to reach an accurate diagnosis. By using Stratipath Breast, clinicians can diagnose with the support of prognostic information, while reducing time and laboratory costs,” says Johann Hartmann, professor of pathology at Karolinska Institutet, Stockholm, and co-founder of Stratipath.

Histological tumor grade is a strong prognostic predictor of breast cancer. A classification of invasive breast cancer is performed on all invasive breast cancers based on morphological assessment, according to the Nottingham Histologic Grade (NHG), resulting in the low to high-risk NHG categories 1, 2 or 3. But currently, more than 50% are classified of all breast cancer patients as being at intermediate risk (ie, NHG 2), providing little clinical benefit for treatment decisions. Excessive and indirect subsequent treatment of patients with early breast cancer has become one of the major challenges faced by clinicians, and clinical decisions often depend on expensive molecular assays that are inaccessible to the majority of patients.

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Using deep learning, Stratipath Breast enables cancer detection and classification of intermediate-risk tumors into low- and high-risk groups, based on tumor morphology associated with the grade. Stratification comes from a rigorous scientific development and validation process using multi-source real-world data sets, which include histopathological images and associated clinical outcome data.

The system measures risk-related morphological patterns locally in the image and collects this information across the area of ​​tissue analyzed to determine whether a tumor belongs to a high- or low-risk group. Results from Stratipath Breast provide prognostic information and are intended to be used as a decision support tool, along with other clinical and pathological information.

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Stratipath Breast provides optimal workflow through integration with leading digital pathology solutions. It can also be used on its own, via the Stratipath customer web portal. Access to Stratipath Breast will be provided as a software as a service solution, by subscription or payment when using the form. Do not shop in the United States.

About Stratipath
Stratipath is an affiliate of the Karolinska Institutet in Stockholm, Sweden, bringing groundbreaking research in artificial intelligence and precision medicine to clinical use. The company was founded in 2019 by Johann Hartmann, MD, PhD, Matthias Rantalinen, PhD and Fredrik Witterhall with the goal of radically improving cancer treatment decisions and patient outcomes. Stratipath offers a precision AI diagnostic solution for healthcare and could provide a fast track for pharmaceutical and biotech companies to identify patients who are most likely to benefit from new treatments.

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2022-06-01 08:08:25

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