“The main advantage for radiologists is that AI enables automated prioritization or highlighting of patients who need urgent attention,” Pooja Rao, R&D head and co-founder of Qure.ai, told HCB News. “The radiology work list can often be long, especially at night, and this tool can help direct radiologists’ attention to critical cases. The highlighting and quantification of abnormalities both save time for the radiologist.”

In May, the startup entered into a three-way partnership combining machine learning and telemedicine, when it agreed to integrate its chest X-ray technology with health IT player Telerad Tech’s RADSpa (T2), a proprietary RIS PACS platform provided worldwide by the service, Teleradiology Solutions (TRS), speeding up the return of diagnoses of X-ray and CT scans at a reduced cost.


“Teleradiology improves patient care by allowing radiologists to provide services remotely. This is particularly important when a subspecialist is needed,” Warier told HCB News. “Unfortunately, teleradiology cannot solve the fact that imaging procedures are growing approximately 15 percent annually against an increase of only 2 percent in the radiologist population. AI can alleviate this problem by improving the productivity of radiologists through screening and prioritizing cases and providing a first draft report to radiologists.”

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