Empowering Pathologists to lead the way in Digital Pathology
Histopathology stands as a pivotal and intricate scientific discipline with a staggering 70% of clinical decisions on treatment relying on pathological insights. Nonetheless, the challenge of inter-observer agreement in the assessment of certain cancers can be stark with concordance rates plummeting to as low as 55%. Qritive’s cutting-edge AI analysis technology addresses this challenge head on by providing pathologists with rapid and precise interpretations of entire whole slide images within a matter of seconds.
Colon cancer is the third most common cause of cancer-related deaths globally. Our Colon Cancer AI Module helps to differentiate benign from malignant colon tissue.
- Deep neural network trained to identify benign areas from dysplastic and malignant areas on biopsy slides.
- Identify high-risk areas seamlessly and reduce error-prone manual measurements.
Prostate cancer is the second most common cancer in men globally. Our Prostate Cancer AI Module helps to differentiate a wide range of benign and malignancies in prostate tissue.
- Deep neural network trained to identify benign from malignant areas on biopsy slides and grade the cancer.
- Identify Gleason patterns and quantify tumour in tissue to avoid laborious and error-prone manual measurements
QAi COLON Dx
QAi Colon Dx by Qritive is a specialized tool addressing the significance of colon cancer, ranked as the third leading cause of cancer-related fatalities globally. It plays a crucial role in distinguishing between benign and malignant colon tissue, aiding in precise diagnostic interpretations.
Utilizing a sophisticated deep neural network, QAi Colon Dx is meticulously trained to differentiate benign areas from dysplastic and malignant regions on biopsy slides. This technology facilitates the identification of high-risk areas, reducing potential errors associated with manual measurements and ensuring a more accurate assessment of colon tissue abnormalities.
QAi Colon Dx stands as a dependable tool, offering improved detection and differentiation of colon tissue anomalies, thereby enhancing the accuracy of diagnostic evaluations in combating colon cancer.
QAi LYMPH NODE Dx
Lymph Node Dx by Qritive, an advanced AI Module designed to detect metastasis in lymph nodes, a condition present in as low as 1.1% of patients with lymphadenopathy. Leveraging deep learning algorithms, this module is adept at identifying metastatic deposits in lymph nodes, contributing to a more accurate diagnosis for cancer patients.
Lymph Node Dx systematically screens lymph nodes, enabling the identification of both macro and micro metastasis. By doing so, it supports pathologists in producing more precise diagnoses for cancer patients, enhancing the overall diagnostic process. This technology provides valuable assistance in the critical task of identifying metastatic conditions in lymph nodes, aiding medical professionals in their efforts to offer effective and informed care to patients with cancer.
QAi KI67 QUANT
QAi IHC Ki67 Quant is an AI Module designed for the quantitative assessment of Immunohistochemistry (IHC) assays with Ki67 staining.
This module utilizes deep learning and image analysis technologies to achieve precise quantification in IHC tests. Through these technologies, QAi IHC Ki67 Quant ensures accurate identification and classification of tumor cells, offering a detailed analysis of findings for enhanced diagnostic insights. This technology stands as a reliable tool for achieving quantitative assessments in IHC, contributing to a more comprehensive understanding of immunohistochemical test results.
QAi BREAST HER2 QUANT
QAi Breast Her2 Quant by Qritive employs deep learning algorithms to analyze histopathology images for consistent and objective HER2 assessment. Accurate categorization of breast cancer patients based on HER2 expression is crucial for selecting the appropriate anti-HER2 therapy. HER2, a human epidermal growth factor receptor 2, plays a pivotal role in breast cancer diagnostics. Its overexpression or amplification is associated with more aggressive tumor behavior.
This specialized module supports pathologists in precisely categorizing patients into HER2-negative, 1+, 2+, and 3+ groups on HER2 stained IHC slides. This categorization is fundamental in guiding treatment decisions, aiding in the selection of candidates for anti-HER2 therapy. QAi Breast Her2 Quant ensures reliable and consistent assessments, facilitating informed treatment decisions for breast cancer patients based on their HER2 status.
QAi COLON MSI INSIGHT
QAi Colon MSI Insight is an AI module that predicts Microsatellite Instability (MSI) status in colon cancer patients. MSI status prediction is crucial in colon cancer diagnostics, guiding treatment decisions and offering prognostic insights. This tool utilizes advanced AI algorithms to analyze histopathology images, aiding pathologists in accurately predicting MSI status. By providing precise predictions, QAi Colon MSI Insight assists in personalized treatment strategies, potentially improving outcomes for colon cancer patients.