AI Case Study
Infervision successfully annotates lung nodules in scans using machine learning
Infervision is a Beijing startup that trains its algorithms on Chinese hospitals's data. Its system is able to identify lung nodules in lung scans with the use of machine learning. When piloted at hospital, it proved to be very valuable in assisting radiologists with identifying nodules. The startup will also provide software to Wake, a company that operates in the same field but is facing greater difficulty in accessing data due to the tighter regulation in the US in comparison with China,Stanford Children’s Hospital, and other US partners. These partners are meant to provide feedback on the algorithm's recommendations and adaptation top US-sourced data and lung scans.
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"Infervision, a four-year-old Beijing startup, has amassed more than a million scans from Chinese hospitals that it’s using to train and test algorithms. Gathering medical data is much easier for Chinese companies than for their US counterparts, because patient populations are larger and the burden of privacy regulations smaller.
“In the US, particularly for big academic hospitals, you have to go through so many processes and it can take a really long time to access data,” says Yufeng Deng, Infervision’s chief scientist. Chinese institutions do take steps to protect patient privacy, such as anonymizing records used in research, and those protections are becoming stronger, he says. But they are not bound by as many rules and external regulatory processes. “In China it’s less well-defined,” Deng says.
To create its algorithm to identify lung nodules, Infervision gathered more than 400,000 lung scans from Chinese partners, such as leading Beijing research center Peking Union Medical College Hospital. Over two years, it then sent each image for review by three radiologists at its Beijing office. Their annotations created the feedstock to train and test image-processing algorithms, in the same way internet companies train systems to recognize cats, dogs, and people. Infervision has published peer reviewed studies in Chinese and US journals on its algorithms' performance.
Infervision’s software is intended to speed up the work of radiologists, not make diagnoses on its own—Deng says he can’t imagine AI being ready to do that within a decade. The company is in the process of seeking FDA approval to market its product in the US.
In the meantime, it will provide software to Wake, Stanford Children’s Hospital, and other US partners interested in testing the tool for free. The startup has also opened offices in Germany and Japan. In China, Infervision is refining its lung-analysis software to look for other things, like bone fractures and emphysema, and testing algorithms that analyze brain scans for signs of stroke.
At Wake Radiology in North Carolina, roughly 50 doctors scrutinize x-rays and other images for local medical providers. Within a few weeks, they should start to get help on some lung CT scans from machine-learning algorithms that highlight potentially cancerous tissue nodules.
Deng of Infervision says that the startup refined its algorithms with around 2,000 US-sourced images to adapt them to American patients and imaging equipment. Wake and other partners will provide feedback on any errors radiologists spot in its recommendations."
"Gathering a big trove of health data in the US typically requires negotiating with multiple partners, all of whom know their data’s value. That can drive up costs beyond the means of startups without large cash reserves. IBM has spent more than $3.5 billion since 2015 acquiring health care software companies and amassing millions of patient records and billions of images of all kinds of medical conditions. The company has published research on medical-image-processing AI software but not yet launched a commercial service. IBM didn’t respond to requests for comment.
Other countries are trying to use easier access to medical data to boost their own AI industries. French president Emmanuel Macron’s AI strategy announced last year includes a pledge to make data from France’s universal health care system available for AI research. The Canadian province of Ontario is using its single-payer health system to lure more investment into its already vibrant AI R&D scene.
China’s government has also made health care and AI a priority. Support for development of medical uses of the technology is part of a national AI strategy launched in 2017. The country’s over-stretched hospitals are also generally more open to technology that might augment the work of doctors than their counterparts in the US, says David Yuan, a partner at Redpoint Ventures, which invested in Infervision. The startup has around 300 employees and has raised more than $73 million from investors, including the Chinese arm of storied Silicon Valley venture firm Sequoia and leading Chinese venture firm Qiming Ventures."
"In a pilot at Shanghai Changzheng Hospital, two radiologists found that Infervision’s product could dramatically boost their ability to annotate lung nodules, the company says."