Nexus-trained CogniABle integrates technology and clinical expertise to provide accessible and affordable screening as well as treatment solutions for neuro-developmental disorders like autism.
Mental health issues, especially among children, may be difficult to manage, often due to the limited number of clinicians available. Founder Manu Kohli and his team at CogniABle see this as an opportunity where technology can help overcome the deficit and detect neuro-development delays earlier in children. By using machine learning, the Gurugram-based start-up has developed automated early screening and treatment for neuro-development disorders, enhancing the capacity of clinicians and non-experts to make informed decisions. CogniABle has received training at the Nexus Incubator start-up hub at the American Center New Delhi.
Excerpts from an interview with Kohli.
What is CogniABle’s origin story?
I am an engineering and management graduate, with more than 16 years of experience in consulting with clients in the information technology sector.
Since I am married to a child psychologist and special educator, I had always felt the growing need for special needs services in India. However, the big transformation happened for us after our son was diagnosed with autism.
After exploring services in India, the United States and a few countries in Europe, we realized the need for technology to scale up the services, with four major objectives: they should be affordable, they can be used by non-experts, they should be available remotely and data driven.
In 2017, I returned to India and started my Ph.D. at the Indian Institute of Technology (IIT) Delhi. The research work focused extensively on developing affordable and scalable solutions for neuro-developmental disorders, in the area of early screening and affordable treatment. This is when CogniABle was formed.
Could you please describe how CogniABle works?
The CogniABle digital platform has two components focusing on early screening and affordable treatment of autism spectrum disorder. A non-expert can use our screening service at 10 percent of the cost from any remote location by submitting a video using the Internet. The video is automatically analyzed by our artificial intelligence algorithms to make autism screening predictions.
Afterward, a treatment plan is developed by following simple assessment processes. CogniABle offers treatment plans in multiple skill areas of language, communication, academics, social skills and lifeskills, to name a few. The longitudinal progress data is analyzed by machine learning models to customize the treatment plan for the child.
What were some of your biggest takeaways from the Nexus Incubator?
Nexus offered a different perspective to look at the business, which we never had before. Entering the Nexus program is itself competitive and tough. A rigorous 10-week schedule, with a mix of online learning, field work and classroom lectures by Nexus experts, was amazing. Guest and expert lectures on topics such as intellectual property, financing, fundraising were the cherries on top. I also realized that, often, an entrepreneur wants to create a solution for which he is passionate about, however the market may not need it.
How has implementation of the CogniABle platform been so far?
Our innovation has allowed us to develop an artificial intelligence engine to recognize human actions with only 25 percent of the data conventionally used. The innovation has been funded by Government of India’s Department of Biotechnology to develop a digital platform that can screen children for autism from recorded videos.
The treatment platform has been rolled out to a few clinics in India and the United States. We have recently signed up with a leading hospital provider, who will help us scale the treatment platform all over India and globally. In addition, we are rolling out our solution to leading pediatricians and schools in Tier II towns and cities in India, where there are hardly any services available. Our plan is to reach 1,000 users on our platform by March 2020.
Today, the real world problems in the public health domain need innovative solutions based on technology, to bring affordability and scale. One has to really understand the problems, validate them with the community and evaluate the kind of data you may need on which you can apply machine learning models as well as build innovative solutions.
Jason Chiang is a freelance writer based in Silver Lake, Los Angeles.