Health

Umakant Soni,CEO, ARTPARK, Health News, ET HealthWorld

Shahid Akhter, editor, ETHealthworld, spoke to Umakant Soni, Founder and CEO, ARTPARK, to know more about the feasibility of low res X Ray images sent via Whatsapp in determining Covid-19

How does XraySetu compare with RTPCR test?
RTPCR test is the primary Covid-19 test but during the second wave of Covid-19 cases rising across the nation, large-scale testing and early intervention is absolutely critical to save lives. Due to the sheer load on the system, reports of RT-PCR are being delayed whereas CT scans are only available in bigger cities. When we look at the situation in rural parts of the country, there are limited RT-PCR test centres and even for a sample to reach a test centre, it takes one to two days. Hence, quick screening results are important to ensure early intervention and better treatment efficacy.

XraySetu is an accessible WhatsApp based screening service that enables rapid identification of suspected Covid patients using AI algorithms over Chest X-Rays. This allows doctors to identify Covid patients at an early stage and save lives.

XraySetu has been tested and validated with over 1,25,000 X Ray images from National Institute of Health, UK as well as over 1000 Indian patients from first wave, XraySetu has shown excellent performance on open source standard data sets as below:

Sensitivity 1 : 98.86% Specificity 2: 74.74% AUC3: 0.9316

Understanding the rural background, XraySetu has been designed to identify covid positive patients even from low resolution Chest X-Ray images sent over Whatsapp.

1 Sensitivity (True Positive rate) measures the proportion of positives that are correctly identified (i.e. the proportion of those who have some condition (affected) who are correctly identified as having the condition).

2 (True Negative rate) measures the proportion of negatives that are correctly identified (i.e. the proportion of those who do not have the condition (unaffected) who are correctly identified as not having the condition).

3 In general, an AUC of 0.5 suggests no discrimination (i.e., ability to diagnose patients with and without the disease or condition based on the test), 0.7 to 0.8 is considered acceptable, 0.8 to 0.9 is considered excellent, and more than 0.9 is considered outstanding.

Tell us about the development of this platform
We took this idea from Italy where doctors were using Chest X-Ray to detect Covid-19 during the 1st wave. On the other hand, in India, the healthcare infrastructure is uneven and quite sparse in rural areas. We have only 1 radiologist for 10 lakh people in rural India. We realized that AI interpretation can be a big scaling advantage in the healthcare sector in India. For that, we initially started a WhatsApp group for rural doctors, who could send us the image to analyze the same. It quickly hit the ceiling of 255 members, mostly doctors, who were using it for their patients. We then decided to convert it into a simpler chatbot service, which now can be used by any doctor from all parts of India. This platform can also ably detect 14 additional lung-related ailments including tuberculosis and pneumonia alongside others.

Tell us more about the 14 other lung ailments XraySetu detects?
The automatically generated report gives annotated images marking 15 different lung abnormalities along with probability of covid and pneumonia. With more images and data, we believe that we can screen more lung abnormalities accurately as well. Currently, we can figure out atelectasis, cardiomegaly, effusion, infiltration, mass, nodule, pneumonia, penumothorax, consolidation, edema, emphysema, fibrosis, pleural thickening, hernia and Cocvid-19.

What is XraySetu’s accuracy to detect Covid-19 over other available options?
We have evaluated our models with the open Covid-19 data set of NIH, UK and got an AuC of 0.93, which is very good performance for any ML. Our model however is tuned for low resolution phone pictures of X-Rays, which is suitable for WhatsApp based delivery. While RTPCR tests remain the gold standard, in rural India, the major challenge is not only about accuracy, but rather at what time the RTPCR tests become available. The core idea of XraySetu is to give doctors another screening option for Covid 19 and plan early intervention in case of corresponding direct observations, so that lungs are not compromised and lives can be saved. Otherwise we are observing the practice of people being given unnecessary medications and steroids, which are creating another set of problems. XraySetu is getting robust results over well taken Chest Xray images sent over WhatsApp with high sensitivity.

Please tell us more about your collaborators ?
XraySetu is a collaborative effort of ARTPARK , Niramai & IISC.
This joint initiative (ArtPark & IISC) is to promote technology innovations in artificial intelligence (AI) and Robotics to lead societal impact by executing mission mode R&D projects in healthcare, education, mobility, infrastructure, agriculture, retail and cybersecurity, focusing on problems which are unique to India.
NIRAMAI Health Analytix is a Bangalore-based AI startup addressing critical healthcare problems through automated solutions. Winner of multiple international events, NIRAMAI is the only Indian company listed on cbInsights Top 100 AI startups in the world. A flagship product of Niramai is its patented Universal Cancer Screening Method using AI-driven thermal imaging.

XraySetu is a collaborative effort of ARTPARK , Niramai & IISC.

How much funding has ARTPARK received so far?
ARTPARK is an autonomous section-8, not-for-profit company, promoted by IISc and supported by AI-foundry, seed-funded by DST (Department of Science and Technology ) and GoK (Government of Karnataka) to the tune of $32 mn (230 cr) to help translate cutting edge research into solutions that can impact society.

Please tell us about future plans or initiatives around healthcare?
Solutions like Xraysetu can be extended to cover other lung abnormalities with more data and research to empower healthcare infrastructure in rural India. India is planning to spend 64000 cr in next 6 years to revamp the healthcare infrastructure. Instead of building just physical PHCs, we need to think ahead and plan for future Covid like challenges, which have overwhelmed the current infrastructure. We believe that by leveraging recent advances in exponential technologies like AI & Robotics to provide state of art care to everyone is the model that India can embrace. Recent innovations applying exponential technologies like AI & Robotics in prevention, early diagnosis and remote delivery, can be modelled in the form of next generation digital PHCs to take effective care to the last mile. This would be the most effective and cost efficient path for a vast and diverse country like India.

By bringing global talent, industry and academia together at ARTPARK, we can create a model for the next generation of healthcare for India, which is truly inclusive for 1.36 bn people.

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