Wake Radiology is a private radiology practice in North Carolina that specializes in providing high-quality, comprehensive outpatient medical imaging services to the patients. The practice has more than 20 imaging locations throughout the greater Research Triangle Area and has received the highest accreditations possible in the United States from the American College of Radiology (ACR). Infervision has established a good business relationship with Wake Radiology and has deployed the InferRead CT Lung. AI system which is becoming an excellent assistant and an “extra pair of eyes” for the radiologists at Wake Radiology.
Infervision has always been focused on the needs and demands of its clients, tailoring its services to make the diagnostic process more accurate and efficient. InferRead CT Lung.AI is able to quickly categorize and list detailed information about pulmonary nodules of different sizes in a chest CT scan.
Infervision also works hard to cater to the preferences of each radiologist. During the initial trial period, the original version of the InferRead CT Lung. AI detects all pulmonary nodules from each CT scan. Wake Radiology physicians later expressed their preferences to focus on nodules over a specific size (3mm) during the diagnostic process. Infervision promptly modified its system adding functional that displayed nodules over the size threshold consistent with the desired diagnostic protocol and radiologists’ preferences.
"Our goal is to make it easier for our radiologists to improve both their detection and to make them more efficient, which will hopefully improve patient care in general,” said Matt Dewey, CIO at Wake Radiology. Infervision is making the full efforts to help Wake Radiology fulfil this goal. Infervision plans to continue listening to the radiologists’ feedback and strives to provide the most useful tool to them. Infervision’s system is fully integrated into the radiologists’ daily workflow. Within seconds, physicians can access and review the AI results directly through the practice’s PACS interface. Key features of the current Infervision product make it user-friendly, robust, and safe. Infervision is continually designing and polishing its products to fit into the radiologist's daily workflow. This will allow Infervsion's AI products to serve as a reliable assistant for the physicians and for the outpatient image offices to provide the best quality service to the patients.
As part of a video prepared for Infervision 2018 Global AI forum about how the company’s current efforts are helping hundreds of providers, Dewey said. "That's quite an accomplishment, especially in this day and age. Not a lot of us are doing this sort of practicing of medicine. This is absolutely fantastic to have these many people involved in this project in this company." Infervision plans to further support Wake Radiology to reach its goals and deliver excellent services to the patients in this upcoming AI era.
Beijing Infervision is an artificial intelligence high-tech company committed to applying deep learning technology to assist medical image diagnosis as efficient and accurate solutions. Infervision effectively uses various types of medical data to create clinically valued products and promotes pre/cision analysis in the medical field especially in assisted image diagnosis. Learn more at Infervision.com.
About Wake Radiology
Founded in 1953, Wake Radiology is the greater Research Triangle region’s leading provider of outpatient medical imaging. Its physicians have been trained as experts in specific imaging subspecialties to accurately detect and diagnose disease and injury. With freestanding outpatient locations throughout the Raleigh, NC area, Wake Radiology has more than 150 certified technologists and radiologists. The practice also provides imaging services at several area hospitals. Wake Radiology is an independent, locally owned and physician-led practice that actively supports the local community. Learn more at WakeRad.com.
Infervision results shown in InteleRad PACS system. Circular ROIs highlight the pulmonary nodules in each slice of a chest CT scan