AI

KardioLabs

Redefining cardiovascular diagnosis

Redefining Cardiovascular Diagnosis  

AI Powered Quantitative Prognosis & Diagnosis Of Heart

 

 
 
 
 
 
 

We are developing Artificial intelligence based solutions for automated reporting of CT Coronary Angiogram for patients suffering from coronary artery disease. With Generative AI capablities we provide an effective way for you to understand the diagnosis better and easier

Cardiology is a branch of medicine that deals with the disorders related to heart. This includes diagnosis and treatment of congenital heart defects, coronary artery disease, heart failure, valvular heart disease and electrophysiology

Overview

Heart Disease are leading cause of death world wide. One person dies every 34 second in USA from heart disease. 1 out of every 3 death worldwide is due to Cardiovascular Disease. American College of Cardiology recommends CTCA as front line test for patients with CAD.

695,457

TOTAL CARDIAC MORTALITY 2021

70%

considered low risk by clinical scoring 

30%

STENT WASTEFUL IF FFR NOT USED

84%

INCREASE IN CTCA FROM 2010

65%

INVASIVE TEST HAVE NO BLOCKAGE

Deep Learning Solutions

 

Gold standard is to determine coronary artery diseases by team of cardiologist and radiologist. It is very invasive, costly and time-consuming process.

 

Our AI based approach use the still and cine images of CT angiogram and detect the blockages and coronary artery disease saving, time, cost and better decision making for healthcare provider (cardiologists) and patient.

Our PARTNERS say about us

Testimonials

KardiolabsAI have developed a novel AI-based medical diagnostic product that has the potential to radically transform and advance cardiac diagnosis by augmenting human performance, advancing the capacity of radiologists and cardiologists, reducing errors and variability, saving time and reducing costs. KardiolabsAI is an alumni of ECHO incubator at Ted Rogers Centre of Heart Research and University of Toronto. 

TBU

TBU

         Product

Klassifier 

Stenosis Detection and Quantification

Kalcium

 
Calcium Scoring for Chest CT and Cardiac CT

Kwantifier

Deep Learning powered solution for Quantitative Prognosis of Cardiac Diseases with
Virtual FFR

one stop solution

KardiolabsAI

our in house built deep learning Solution offers faster diagnosis , reduce cost , is fully automated and results in faster decision making to improve patient care and save lives. integrated with a conversational bot to provide indepth infromation on the diagnosis. 

Our People

Sudhir Rathore

MBBS, MD, FRCP, FACC, FESC

Has over three decades of rich experience in both in clinical cardiology and clinical research in India, Japan and UK. He has been working as Consultant Interventional Cardiologist at Frimley NHS Foundation NHS Trust, Surrey, UK for last 10 years.

Samir Rathore

Samir Rathore has over 27+ years of rich experience in leadership roles in varrious companies in India, Malaysia, United Kingdom and United States. Samir complete his MBA from Indian Institute of Management (IIM), Ahmedabad, India in 1998. 

Ashish Gautam

Btech IIT D

 

Ashish Graduated from IIT Delhi. His area of research is Deep Learning and Computational Geomatry. 

Carol Coplan

General counsel and business development executive with wide-ranging experience in high tech, healthcare and real estate. More than 20 years of experience helping rapidly growing companies scale and grow.

Mia Sun

Mia has 6 years working experience involved with data analysis in various industries, proficient in data processing, predictive modeling, statistics. With education in engineering.

Sri Ayangar

MBBS MS (General Surgery) FRCS FRCR 

Sri is thoracic radiologist. consultant at Birmingham City and Sandwell Hospital NHS trust in 2012. His major clinical interests are in chest and cardiac radiology.

Vijay Subramanya

Vijay is a Ph.D. student at the University of Waterloo, Canada, with a research focus in graph algorithms. He has published research papers in verious prestigious confrences.

Vikas Gupta

Vikash Gupta is an Assistant Professor at the Department of Radiology at Mayo Clinic, Florida. He is a contributor to the MONAI framework for medical imaging and AI. He has been a contibutor and reviewer to confernces  and journals like MICCAI, ISBI, Transaction on Medical Imaging, and Medical Image Analysis

   Our Contributors

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Address:

11

188 Cumberland St. Toronto

 

11250 Old St Augustine Rd Ste 15-262

Jacksonville, FL, 32257

 

Email:

contact@kardiolabs.ai