In India, each year, approx. 220,000 deaths are reported due to Tuberculosis. Between 2006 and 2014, the disease cost the Indian economy USD 340 billion. This public health problem is the world’s largest tuberculosis epidemic. India bears a disproportionately large burden of the world’s tuberculosis rates, as it continues to be the biggest health problem in India. It remains one of the largest on India’s health and wellness scale. India is the highest TB burden country with World Health Organization (WHO) statistics for 2011 giving an estimated incidence figure of 2.2 million cases of TB for India out of a global incidence of 9.6 million cases.
Compare India to Canada, where there are about 1,600 new cases of TB every year. Citing studies of TB-drug sales, the government now suggests the total went from being 2.2 million to 2.6 million people nationwide. On March 24, 2019, TB Day, the Ministry of Health & Family Welfare of India notified that 2.15 million new tuberculosis patients have discovered only in 2018.
Dr. Shibu Vijayan, Director TB/HIV/PATH India, speaks in the informational video that currently, it takes around 2 months for the patient to get diagnosed from the symptoms. The time required is huge when related to a person’s illness and cure as without knowing the exact problem, the particular cure process can’t be prescribed by the doctor. Thus increasing the chances of worsening the health of a patient.
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.
A Mumbai-based healthtech start-up, Qure.ai, has developed an artificial intelligence (AI)-powered technology that can examine X-rays, MRIs and CT scans, identify patients with diseases like tuberculosis or stroke, that can be traced with these diagnostic techniques and prepare accurate reports in no time.
The AI technology involves the application of deep learning algorithms to detect and highlight abnormalities in medical imaging like chest X-rays, MRIs and CT scans. It aims to significantly scale and improve the diagnosis of diseases, especially TB, in the country.
Qure.ai was cofounded by AI scientist Pooja Rao and IIT alumni Warier in 2016. Warier, who also works as the Chief Data Scientist at Fractal, had earlier founded AI-powered personalized digital marketing firm Imagna Analytics, which was acquired by Fractal Analytics in 2015.
Warier has a Ph.D. and an MS in Operations Research from Georgia Institute of Technology, while Rao, who heads R&D at Qure.ai, has a Ph.D. from the International Max Planck Research School for Neuroscience focussed on neuroscience and machine learning.
The company’s mission is to use artificial intelligence to make healthcare more accessible and affordable. Their core team combines deep learning expertise with clinical, scientific and regulatory knowledge. The advisory panel consists of radiologists, other doctors and public health experts. They work with these specialists to define clinically relevant problems and design real-world solutions.
The patient outcomes are highly dependent on the time is taken to initiate treatment. Patients treated within 90 minutes from a stroke caused by traumatic brain injury (TBI) onset have an increased odds of improvement at 24 hours and favorable 3-month outcome compared to patients treated later than 90 minutes.
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 start-up 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.
Qure.ai’s model involves selling its diagnostic tools directly to hospitals, collaborate with health-centric non-profits, and medical devices companies among others. It claims to have implemented its solutions in more than 12 countries including India, Philippines, US, France, Canada and some parts of Africa.
In India, the company collaborated with NITI Aayog, Piramal Foundation’s Piramal Swasthya initiative, and PATH NGO. Qure.ai’s chest X-rays solution has been deployed in Uttar Pradesh and Rajasthan where it claims to have reached more than 10K patients.
The chest X-ray tools have also been deployed to select primary health care (PHC) centers in Indian villages to speed up screenings of diseases such as tuberculosis screenings. India has the highest (28 Lakh cases in 2016) number of tuberculosis (TB) cases in the world, accounting for a quarter of the global TB cases. The company claims that its solution takes less than three minutes to detect an abnormality with a 95% accuracy rate as compared to the traditional timing of at least 20 minutes.
While Qure.ai is an Indian company, globally AI in healthcare is dominated by large conglomerates such as IBM and Google AI. Despite the relatively lower prevalence of innovative AI solutions for the Indian market, the healthcare and medtech sector is expected to grow to a $372 billion industry by 2022. Obviously, this means there’s a largely untapped opportunity for the healthtech start-ups globally, and you can be the one contributing to our health sector by providing various innovative ideas and products, thus making us healthy and disease-free. If they can do it, you too can!!!
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Edited by Saket Dethe