One of the biggest challenges in curing many diseases is getting the right diagnosis as early as possible. While there are diagnostic imaging options such as MRIs and CT scans, besides the ubiquitous X-rays, not all patients receive an accurate, timely diagnosis. The volume of data and complexity is also increasing substantially as opposed to the number of doctors who can interpret them. Qure.ai, a start-up founded in 2016, is trying to change this with the help of algorithms which can automatically read most of the easier, high-priority radiology scans, allowing the radiologists to spend more time on cases which are complicated. Qure.ai\u2019s new solution can automatically generate abnormality reports. These automated reports are a first-to-market capability in the AI and radiology category, helping radiologists and hospitals prioritise care, make smarter and faster diagnoses and reduce costs. To date, Qure.ai has delivered AI-powered chest, abdomen and musculo-skeletal image interpretation technology apart from head and brain CT scans. \u201cQure.ai applies technology such as Deep Learning or deep neural networks to medical images to develop algorithms that can identify disease patterns. Qure.ai\u2019s Deep Learning algorithms are deployed as software, which is compatible with any X-ray, CT scan or MRI machine. These help in classifying radiology images as normal or abnormal, diagnose disease and highlight abnormalities that may otherwise be overlooked. \u201cQure.ai\u2019s new head CT scan technology rapidly screens scans in under 10 seconds to detect, localise and quantify abnormalities, as well as assess their severity,\u201d says Prashant Warier, CEO and co-founder, Qure.ai. One of Qure.ai\u2019s applications detects and precisely quantifies a lung disease called idiopathic pulmonary fibrosis (IPF). Previously, radiologists were only able to monitor progress of IPF at one-year intervals. With Qure.ai\u2019s algorithm, even tiny changes in IPF progression can be detected and quantified, and patient progress monitored more frequently. With tuberculosis detection largely dependent on diagnosis based on x-rays, Qure.ai\u2019s AI solutions can help machines automate diagnoses or provide preliminary diagnosis. Qure.ai, co-founded by Warier and Pooja Rao, a medical practitioner as well as AI scientist, has been funded by Fractal Analytics, a global leader in artificial intelligence and analytics. As part of its commitment, Fractal Analytics will be investing upto $30 million over the next four to five years. Currently, Qure.ai\u2019s products are deployed in five radiology centres, with three in Mumbai and two outside India. The product plugs directly into the radiologists\u2019 workstations, so there is no additional training required for them to learn to use the software. Depending on the modality (X-ray or CT scan), prices range from Rs 120-300 per scan.