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Avyantra: Using machine learning to facilitate early treatment to infants with neonatal sepsis

Avyantra Data Science+AI India
Dec 09 , 2019
Head nurse, Priyanka Singh, assists a new mother, Bindiya Devi on how to handle her new born son before she feeds him, at Prabhawati Hospital, Gaya, Bihar.
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Data Science+AI


Amount invested $128,233 USD Funding Status graduated early period Founded in 2017 by Hyma Goparaju & KVKLN Rao
Female Founded
DPG Certified

In December 2018, the UNICEF Innovation Fund onboarded its largest round of portfolio investments of thirteen startup companies using frontier technology solutions to address complex challenges and create fairer opportunities for children and young people. Avyantra joins the Data Science/ Artificial Intelligence portfolio these investments are working with sophisticated applications of computer science including data mining, data processing, machine learning, artificial intelligence, and others, to help make the world a better place.

Avyantra Health is building a platform to help address neonatal sepsis, a blood infection that occurs in infants younger than 90 days old.

According to a recent report by UNICEF,  newborns in India are affected by numerous life threatening challenges such as neonatal sepsis. Detection of the condition is critical for positive birth outcomes but the lack of a specific diagnostic test for neonatal sepsis presents a significant challenge to treating infants as quickly as possible.    

Traditional methods need to be complemented with techniques deploying deep learning methods to increase the speed and accuracy of treatment (as the first 24 to 48 hours are the most critical in order to prevent infections).

Our team hopes to tackle this alarming mortality rate by tapping into cutting-edge technologies in order to create more equitable healthcare for newborns in India.

Our application uses a cloud-based data analytics platform and conducts diagnosis using machine learning.

Through inputting different neonate data points, the platform generates a predicate score that doctors can use in their diagnosis of neonatal sepsis.  These methods are expected to significantly improve accuracy and reduce the time of diagnosis, thereby facilitating early treatment to the babies affected by neonatal sepsis. Using machine learning and data analytics to power our platform allows us to deploy our solution to different regions of the country in a fast and cost-effective way.  Going forward we plan to scale our solution using AI techniques such as deep learning.

A New born baby is being taken care in well equiped Mother & Newborn Care unit in GMERS, Gandhinagar, Gujarat, India.Unicef India/ John Edwards View more with similar tones

Open Source

An Open Source platform provides an opportunity for us to share and learn key insights and experiences with the vast global community of data scientists. These learnings will help us not only to improve our solution but also provide us with space and audience to test, build and deploy a robust solution in a short timeframe.

Team and Diversity

The team is comprised of people with experiences ranging from marketing, healthcare, IT, and analytics. The founder is an IT professional with a passion to build healthcare solutions and has undergone clinical immersion for more than 500 hours. The co-founder is a marketing professional who is undergoing her PhD and is committed to using her experience and learnings in healthcare.

Diverse teams bring in various dimensions and perspectives which help us refine and strengthen our processes and solutions. Most importantly, complex healthcare problems such as neonatal sepsis require multiple skills and understanding that can be achieved by working with diverse teams.

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