Digital Pathology & AI, London, 2021

We talked about how Deep Learning networks trained on histopathological ground truth can increase the accuracy of non-invasive diagnostic technologies like mpMRI and provide a potential translational approach to better staging and therapeutic planning.


Pathology Visions 2021

Abstract title: A Deep Learning method for Tumour Region Identification and Tumour Proportion Score Estimation for PD L1 Expression in Non Small Cell Lung Carcinoma

We propose a computational technique using Deep Learning for detecting the cancer regions and calculating the Tumor Proportion Score (TPS) for PD L1 expression, in immunohistochemically stained sections from Non Small Cell Lung Carcinoma (NSCLC).

8th STP-I Annual Conference 2021

We demonstrated AIRADHI, an Image Management System for Preclinical Digital Pathology Workflows and Peer Reviews, at STP-I 2021.

Intelligent Health AI, 2021

Chaith Kondragunta, CEO of AIRA MATRIX, spoke at IHAI 2021 about the usage of deep learning applications in pathology.

Tech Talk


AIRA MATRIX presented two papers at the ARVO: IMAGING IN THE EYE CONFERENCE on May 13,2021.

The first presentation discussed a deep learning-based automated screening system capable of detecting and diagnosing diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD), and few other pathologies in retinal images.

The second presentation introduced a deep learning tool for the early detection and grading of Diabetic Macular Edema (DME) using color fundus images, achieved by performing a LEsion Aware Prediction (LEAP) by segmenting hard exudates (HE).

Event Website


AIRA MATRIX hosted a session titled, “Demystifying Deep Learning for Pathologists” on June 25th, 2019 at the Society of Toxicologic Pathology (STP) 38th Annual Symposium.

4th Joint European Congress of the ESVP, ESTP and ECVP

AIRA MATRIX presented an informative session on optimizing preclinical pathology reporting using AI techniques. The session familiarized participants with deep learning (DL) modules that help speed up complex workflow processes in toxicologic pathology.


AIRA MATRIX announced the development of an Artificial Intelligence based image analysis solution for Rapid On Site Evaluation (“ROSE”) of EBUS-TBNA samples in collaboration with Dr. Suman Paul, Specialist Registrar in Respiratory Medicine, Warrington and Halton Hospitals NHS Foundation Trust.


By contuining to use this website, you consent to the use of cookies in accordance with our Cookie Policy

Got It