Infervision, a company that uses Big Data and artificial intelligence (AI) to improve medical diagnoses, recently released the InferRead CT Chest, a product concept that can detect four different conditions with one set of chest scans.
The InferRead CT Chest allows doctors to review an image once in order to perform multiple disease screenings in the chest. These screenings include lung nodule screenings, chest fractures, bone metastases and bone tumor screenings, chronic lung disease screenings, and cardiac calcification screenings.
Now, the lung nodule screening can provide a complete view of the nodule, and includes showing the volume and density. Physicians can also compare these screenings to other similar cases from a case report bank in order to get better diagnostic information.
Infervision is also introducing another product concept to help manage emergency conditions, including stroke and bone fractures. Doctors will be able to use AI for faster diagnosis and to determine different treatment options. This concept of using AI to improve emergency room workflow is currently being tested in hospitals in China.
“At the end of the day, our goal is improving a person’s life,” said Chen Kuan, Found and CEO of Infervision. “We simply want to use our technology to act as an aide and help doctors perform at the highest level. Doctors are already working long hours with many cases to manage. Now, we can provide more comprehensive all-in-one reports which will streamline radiologist workflow, and which may be life saving for many patients.”
Infervision hopes to help doctors gain access to more accurate reports, while performing emergency actions with better precision. Recently, Infervision tested their technology and compared it to a group of radiologists in a head-to-head report-reading experiment. According to Infervision, the AI-CT predicted more accurately than radiologists in every category.
“Infervision believes that technology plays an important role in AI development, but technology is not the only requirement for developing excellent products. Clinical workflow integration, robustness of the AI model, as well as scalability are all important elements to succeed,” said Kuan. “Infervision’s R&D team will work closely with the radiologists and physicians from various medical institutions around the world to understand their needs and challenges with regard to AI solutions so we can continually improve and develop the best-in-class AI solutions.”
