There are several other startups that are enabling software with deep learning that could considerably improve diagnostics segment, thus making way for better and effective treatments.

AI in India

Taking a cue from its global counterpart, the Indian healthcare sector is witnessing a gradual adoption of AI in its services. For instance, SigTuple, an AI startup, was founded in 2015 with the aim of improving diagnostics and treatments offered by healthcare centres in the country. The company has created Shonit, an AI based digital system that analyses the images of blood cells to diagnose the disease.

“When I first heard about digital image analysis using AI and its intended use in routine haematology reporting, I was very excited, but simultaneously I had my critical views,” says Dr Preethi S. Chari, consulting pathologist, Anand Diagnostics Laboratories, in her blog.

IBM Watson for Oncology (Image courtesy: IBM)
IBM Watson for Oncology (Image courtesy: IBM)

In her blog, she explains that Shonit views and then analyses the morphology of blood cells, identifies large platelets, malarial parasites and other crucial information that makes the final report extremely informative. “The intended use of this software in our laboratory is to analyse all cases for which slides are made and viewed on the computer (instead of a microscope). The images and other morphological parameters are correlated with the counts obtained by the cell counter. In most cases, a good correlation can be found. For example when the cell counter-flags for monocytosis and Shonit shows a high monocytes count along with images of monocytes, the report can be finalised at this level. If there is a discrepancy or suspicion of abnormal or atypical cell, the slide is viewed under microscope,” she adds.

Another startup Practo is betting big on AI to better assist doctors in their clinical assessments. The company, which has raised US$ 55 million, will be using part of its funding for research and development in AI for doctors.

Then there is healthcare startup HealthGenNext that uses AI to detect diseases using deep learning techniques.

However, while several startups are coming up with solutions using AI for the healthcare industry, the willingness to accept these solutions is still nascent. Besides, affordability is a major factor in adoption of these solutions. To conclude, once startups are able to provide these solutions at an affordable price, we will witness a paradigm shift in our healthcare industry.

Purba Das, senior business journalist, EFY


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