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Envision Healthcare Radiologists Uses AI to Improve Patient Experience

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A leading medical group, Envision Healthcare, has announced the successful use of artificial intelligence (AI) to enhance clinical evaluations and deliver high-quality, patient-centered care. A new AI program has been designed to assist radiologists with the detection, classification, and diagnosis of diseases, and is capable of detecting several common, life-threatening medical emergencies: intracranial hemorrhages, pulmonary embolisms, and cervical spine fractures.

Maria Rodriguez, MD, Chief of Radiology at Envision Healthcare, said, “Our radiology team does a tremendous job of reading scans to evaluate and diagnose millions of patients’ conditions with accuracy and timeliness. We are continuously reviewing best practices and ways to advance the delivery of high-quality care. AI technology is one of the tools we can use to complement our clinical expertise, so we can continue achieving accurate reads and providing the right care to patients at the right time, ultimately saving their lives and improving overall health outcomes.”

Envision’s proprietary platform is being used to deliver this technology to radiologists. The use of AI software for medical image analysis assists radiologists in prioritizing time-sensitive conditions like strokes and perforated bowels while providing additional support in analyzing medical images. Artificial intelligence can improve diagnosis accuracy and prioritize acute cases so that patients receive more timely care according to their condition and level of acuity.

Chris Granville, MD, Envision Healthcare radiologist leading the medical group’s AI implementation, said, “AI has become invaluable, enabling radiologists to maintain and improve the quality of care we provide while meeting the growing demand for our expertise. As one of the largest U.S. radiology groups caring for millions of patients from different backgrounds and locations, we have a highly unique and diversified dataset, which is integral to augmenting deep learning within AI. While we continue strengthening our AI application to improve our workflows and patient care, our ultimate goal is to use our dataset to help advance the AI community at large.”

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