AI DIAGNOSTIC MODULES​
QRITIVE’S EXTENSIVE PORTFOLIO OF AI MODULES ACROSS DIVERSE DIAGNOSTIC AREAS
Qritive offers a suite of AI-powered diagnostic modules designed to support pathologists across a broad range of clinical applications—from cancer diagnosis and metastasis detection on Hematoxylin and Eosin (H&E) stained whole-slide images (WSI) to biomarker analysis on immunohistochemistry (IHC) WSI.​
These modules deliver fast, accurate, and reproducible results by analyzing entire whole-slide images within seconds. Seamlessly integrated into digital pathology workflows, they help reduce interpretation variability, streamline reporting, and support confident decision-making across different tissue types and diagnostic challenges.​
Explore our AI module portfolio tailored to meet the needs of modern pathology.
CLINICALLY PROVEN & PUBLICATION SUPPORTED
OUR AI DIAGNOSTIC MODULES ARE SUPPORTED BY ROBUST CLINICAL EVIDENCE AND PUBLISHED IN PRESTIGIOUS MEDICAL JOURNALS AND CONFERENCES, ENSURING ACCURACY AND RELIABILITY
QAi Colon Dx
Colon cancer is the third leading cause of cancer-related deaths globally, highlighting the critical need for accurate and early diagnostic support. QAi Colon Dx addresses this need by assisting in the differentiation between benign and malignant colon tissue, enhancing diagnostic precision in pathology assessments.
Powered by deep learning technology, QAi Colon Dx is trained to accurately identify benign, dysplastic, and malignant regions on digitized colon biopsies. By highlighting high-risk areas and supporting consistent evaluations, it helps pathologists reduce variability and potential errors associated with manual interpretation.
Through objective and reproducible analysis, QAi Colon Dx improves diagnostic confidence and contributes to more timely and accurate identification of colon tissue abnormalities.
QAi Lymph Node Dx
Accurate detection of lymph node metastasis is critical for cancer staging, prognosis, and treatment planning. Identifying micrometastases, in particular, requires detailed examination and can be time-consuming. QAi Lymph Node Dx addresses this clinical need by assisting pathologists in detecting both macro- and micrometastatic deposits, improving the accuracy and efficiency of cancer diagnosis.
​Leveraging a deep learning approach, QAi Lymph Node Dx directs attention precisely to areas of concern, significantly reducing the time required for metastatic screening. It supports faster, more consistent pathology reporting and aids clinical decision-making for patients with metastatic disease.
QAi Ki-67 Quant
QAi Ki-67 Quant applies advanced image analysis techniques to deliver consistent and objective quantification of Ki-67 expression in IHC assays. Accurate measurement of Ki-67 is essential for assessing tumor aggressiveness and guiding treatment decisions.
QAi Ki-67 Quant enables precise identification and quantification of Ki-67-positive tumor cells on IHC WSI, helping pathologists reduce variability and improve consistency in scoring.
By providing reproducible and standardized analysis, Qritive’s solution supports greater confidence in diagnostic and treatment decisions involving tumor proliferation markers.
QAi HER2 Quant
QAi HER2 Quant leverages deep learning algorithms to analyze histopathology images for consistent and objective HER2 assessment. HER2, or human epidermal growth factor receptor 2, is a key biomarker in breast cancer, and its overexpression or amplification is associated with more aggressive tumor behavior. Accurate evaluation of HER2 expression is crucial for selecting appropriate anti-HER2 therapies.
Building on this assessment, QAi HER2 Quant enables precise categorization of patients into HER2-negative, 1+, 2+, and 3+ groups on HER2-stained IHC WSI. Reliable HER2 scoring is essential for guiding treatment decisions, and QAi HER2 Quant ensures consistent and reproducible assessments to support optimal patient management.
QAi PD-L1 Quant
QAi PD-L1 Quant aims to provide consistent and objective evaluation of programmed death-ligand 1 (PD-L1) expression in histopathology images. PD-L1 is a critical biomarker used to predict patient response to immune checkpoint inhibitor therapies across various cancer types, where accurate expression analysis plays an important role in therapeutic decision-making.
Through standardized scoring of PD-L1 expression on IHC WSI, QAi PD-L1 Quant is intended to assist healthcare professionals in making more informed choices when identifying candidates for immunotherapy treatments.