Qure.ai develops deep learning solutions that read and automatically interpret medical images like X-rays, CT scans and MRIs. The company has trained algorithms to perform tasks that were previously the domain of highly trained doctors. The algorithms help free up physician time, prioritize cases that need special attention, and enable more accurate diagnosis, leading to better outcomes for patients, at lower costs.

Qure.ai was founded to address the need for affordable and accessible diagnostics with deep learning technology. The company is building a system that captures the combined expertise of hundreds of doctors, to create better, faster, and wider-reaching diagnostics.

Qure.ai was founded in 2016 with a small core team and has since grown to its current size of 20 people. The team combines deep learning expertise with clinical, scientific and regulatory knowledge. Qure.ai’s advisory panel consists of radiologists, other doctors and public health experts.

Deep Learning Powers Qure.ai Solutions

Qure.ai develops deep learning algorithms that understand and interpret X-rays, CT scans and MRIs with unprecedented accuracy; providing faster, more accurate diagnosis and better patient monitoring. Qure.ai’s product is a radiology diagnostic aid based on artificial intelligence. The company’s flagship applications are chest X-ray abnormality detection and brain CT analysis for emergency care.

Qure.ai’s algorithms help doctors and radiology centers be more efficient and more accurate with their diagnosis.  When machines perform basic image interpretation tasks with the help of Qure.ai solution, doctors can focus on spending more time with patients. This leads to better diagnostics at lower costs for the healthcare provider.  The ultimate beneficiary is the patient, whose diagnoses can be done faster.

Meet the Innovators

The company is headed by Prashant Warier, CEO and Co-founder; and Pooja Rao, R&D Head and Co-founder.  Prashant is an artificial intelligence expert and an experienced entrepreneur. Prior to Qure.ai, he founded Imagna Analytics, a company that was acquired by Fractal Analytics in 2015. He has also worked with SAP and was instrumental in building their data science practice. Prashant has a Ph.D. and MS in Operations Research from Georgia Institute of Technology and a B.Tech. from IIT Delhi.

Pooja Rao is a medical doctor, with a history of applying machine learning to data-heavy medical problems. She has previously worked as a data scientist and bioinformatics scientist (GoDataDriven, the Netherlands, and Genomescan, the Netherlands). Pooja has a Ph.D. in Neuroscience from the Max Planck Institute, Germany and an MBBS from Maharashtra University of Health Sciences, Pune.

“Over the last 5 years, we are seeing the applications of deep learning growing exponentially. Deep neural networks have revolutionized the way machines learn. This technology is rapidly breaking down barriers between tasks that require human expertise, and those that can be automated. This has been made possible by a combination of advances in technology, availability of processing power in the form of GPUs, and importantly – large amounts of data,” said Pooja.

“While the algorithms and technology are gradually being commoditized – the most accurate algorithms will be the ones that have been trained with the largest amounts of well-labeled data. For artificial intelligence to be adopted in areas like healthcare, it must provide measurable benefits to users, “she added.

Awards and Recognitions

Since its inception, Qure.ai has been recognized for pioneering artificial intelligence in healthcare and has won awards such as the NVIDIA Social Innovation Award for top AI companies – Dec 2016, Netexplo 2017 award – Paris, in partnership with UNESCO, for being one of the 10 most promising global digital initiatives – April 2017 and also Yourstory’s TECHSPARKS Tech 30 2017 – September 2017. Recently, Qure.ai’s head CT scan solution qER received a NASSCOM Game-Changer award for AI innovation.

Turning Challenges into Success

Commenting on the challenges Pooja said, “Deploying technology for doctors is challenging, for various reasons. In the healthcare space, algorithm accuracy, and patient safety is critical (and rightly so). This means that regulatory approvals (CE and FDA) are key milestones for healthcare companies. We have just received CE certification for our chest X-ray product, and we expect to have similar regulatory clearances for our other products, including FDA by year-end”.

“At the end of the day, success for Qure.ai is defined by how we can help provide diagnostic access to areas without trained clinicians, how much time we can save for doctors and how many patients we can impact as a result,” she mentioned.