
China is pushing ahead in artificial intelligence, including applications to improve people’s health. But industry insiders say there are numerous challenges that stand in the way of automation in the healthcare sector.
“No matter how advanced our algorithms are, if we don’t have a high-quality data, the training results will be biased,” Chen Tong, chief health officer of IBM Greater China, said last week during a healthcare panel at CES Asia in Shanghai.
He added that good data should be well-structured but right now, there is too much “noise” in China’s healthcare databases, referring to unclear information contained in patient records. “We have hundreds of thousands of reports but only thousands are available for deep learning,” he said.
The industry faces a multitude of other issues, insiders say, including siloed information, the inability to transmit data effectively, and privacy concerns, all of which make implementation difficult.
John Gu, executive vice president and chief digital officer of Wuxi Nextcode, a genomics startup, said at the same event that algorithms, which need to be trained with a large amount of data, can’t make accurate decisions if hospitals are not willing to share information. Gu said healthcare facilities haven’t figure out a way to distribute the benefits that come with sharing data, as it’s hard to measure the contributions of individual hospitals.
Sharing data creates its own problems. “The privacy issue is still sensitive when it comes to the medical industry,” Ryan Zhang, CEO of oncology data platform LinkingMed, said at the event. “Hospitals are reluctant to share data since they don’t want to risk leaking personal information,” he added.
To ease hospitals’ concerns, China’s premier Li Keqiang last week signed regulations governing the management of human genetic information, aiming to clarify how to regulate the use of medical data, protect patient privacy, and preserve Chinese people’s genetic information.
According to the documents, China supports using human genetic information for scientific research, developing the pharmaceutical industry, and improving medical treatments. The use of some types of genetic information, including those that relate to “important families and special regions” (our translation), requires administrative approvals. No definition for this category has yet been given.
Zhang said that edge computing technology could be a good way to address privacy concerns by analyzing the data on a private server or device, rather than a public cloud.
Another problem is transfer speeds, particularly when it comes to big datasets for training algorithms in healthcare. “Gene data is far larger than all the data human beings produce on social media. To analyze it, a desktop [computer] is never enough, but 5G provides a solution by [efficiently] uploading the data to a more powerful server,” Chen said.
Ryan Li, head of Commercial Innovation & Alliance at Merk, one of the largest pharmaceutical companies in the world, said during a panel at the same event that 5G can help more patients from remote areas access the same medical resources as those in big cities such like Beijing and Shanghai.
The Chinese government issued its first 5G licenses for commercial use earlier this month. The move came shortly after Washington continued its offensive against Chinese telecommunication firm Huawei due to fears it could pose national security risks as a result of possible links to the Chinese government.
China’s smartphone companies including Huawei, ZTE and Xiaomi, and telecom operators like China Mobile, China Unicom, and China Telecom have all made public their ambitions to begin deployment of infrastructure and devices once licenses were granted.
“5G brings completely new possibilities for remote telemedicine, community healthcare, and remote surgery,” Zhang said.