|Tencent AI Medical Imaging predicts several diseases, including lung cancer, diabetic retinopathy, and esophageal cancer with a higher accuracy rate / Photo Credit: Sergey Nivens via 123RF|
China is one of many countries heavily investing in artificial intelligence for healthcare. Executive Ma Huateng, founder and chief executive of Chinese internet-based technology and cultural enterprise Tencent, stated that they are using the technology to improve healthcare efficiency. They are also considering if AI can help patients and reduce the financial and psychological burden on their families by integrating it into the healthcare system.
The World Economic Forum, an independent international organization committed to improving the state of the world by engaging business, political, academic, and other leaders of society to shape global, regional, and industry agendas, reported that almost 80% of hospitals and medical companies in China are either planning to or have already carried out medical AI applications. Also, more than 75% of medical institutions believe that these applications will become popular in the future.
The growth of AI applications in China’s healthcare sector is driven by the increasing demand for these technologies, especially as population aging has put enormous pressure on its healthcare system. Medical AI plays an integral role in the country, where current healthcare services fall short of the growing demand from an aging population of 1.4 billion.
One of the AI applications that China’s healthcare sector is using is medical imaging. In 2017, Tencent AI Medical Imaging was developed. This system aimed to screen several diseases, including lung cancer, diabetic retinopathy, and esophageal cancer. According to Daxue Consulting, a research firm providing tailored market research solutions with strategic and full-length reports, the AI-powered diagnostic medical imaging service has established cooperation with more than 100 hospitals in China.
Tencent AI Medical Imaging has accuracy rates of more than 97% for preliminary diagnoses diabetic retinopathy, 95% for lung sarcoidosis, and 90% for esophageal cancer. It has assisted doctors in reading more than 100 million medical images and served nearly one million patients.