News

Healthtech Startup Qure.ai leveraging AI for radiology diagnosis

Views: 693
Artificial Intelligence

The healthtech startup Qure.ai uses Artificial Intelligence to detect abnormalities in X-rays, CT scans and MRIs. Its algorithm takes less than three minutes to detect abnormality with 95% accuracy.

Artificial Intelligence (AI) in healthcare is expected to reach $36.1 bn by 2025.

Everyone is talking about artificial intelligence (AI) as the technology that will revolutionise every aspect of human life. Often AI is used as a catch-all phrase to describe future technology, but its implementation and applications are much more diverse than that.

AI is not only helping scientists and researchers find cures through protein-folding to beat cancer or enabling gene editing through CRISPR models, but it’s also supporting the need for early disease detection, which is very crucial in preventive treatment.

In the healthcare market, the commercial use of AI is expected to reach $36.1 bn by 2025, at a CAGR of 50.2% between 2018 to 2025.

AI is already being used to detect early stage cancer symptoms, more accurately than conventional methods such as human doctors peering over MRI scans and X-Rays, looking for anomalies. Machine-learning models and neural networks can help AI detect such anomalies in a fraction of the time taken by doctors. This is especially crucial in the Indian market, given the breadth of its population and the lack of intensive diagnostics in many remote areas.

“The patient outcomes are highly dependent on the time taken to initiate treatment. Patients treated within 90 minutes from stroke caused by traumatic brain injury (TBI) onset have an increased odds of improvement at 24 hours and favorable three month outcome compared to patients treated later than 90 minutes,” according to Prashant Warier, CEO of Qure.ai, who is working with Indian medical institutions and healthcare professions to enable AI-based disease detection for brain injuries.

Not only can it significantly impact the speed and efficiency of disease detection, it also frees up doctors to perform other interventions, instead of spending weeks studying reports and vitals.

“In the status quo, the productivity of radiologists is hampered since there’s no way of automated prioritisation which directly affects patient outcomes and mortality,” Warier added.

Also read: Radiology and Imaging Augmenting Patient Care

Mumbai-based Qure.ai aims to fill this gap by applying AI and deep learning technology to studying radiology images for quick and accurate diagnosis of diseases. The startup claims its algorithms can detect clinically-relevant abnormal trauma findings from X-rays, CT Scans and MRIs in a fraction of the time that doctors typically take.

The company claims to have used more than 7 million data sets to train its AI algorithms, and has validated test results and accuracy of its diagnosis at global institutions such as Stanford University, the Mayo Clinic, and the Massachusetts General Hospital.

Latest News

To Top