From Airdoc to the Industry, China’s Medical Image Reading Startups are Booming

Healthcare, Technology Author: Yingwei Fu Jan 11, 2019 05:39 PM (GMT+8)

On January 10, 2018, Airdoc has received its series B+ financing from Ping An Group and CITIC Securities Company. Healthcare is welcoming the new tech to reform current market and provide better healthcare services.

Person lying on CT-scan machine. Photo: Ken Treloar on Unsplash

As AI and deep learning invasively influence almost industries, healthcare area, which is rich in data accumulation and with mainstream traditional industry structure, is welcoming the new tech to reform current market and provide better healthcare services. AI’s application in healthcare is not unfamiliar for most of us. In past few years, medical image reading has been embracing several startups that develop and use AI to assist radiologist image-reading works. In China, medical image reading startups have become capital chasing.

On January 10, 2018, Airdoc(郁金香伙伴) has received its series B+ financing from Ping An Group (平安集团) and CITIC Securities Company(中信证券). In a capital winter, when most Chinese security companies lowered their 2019 market expectation, the new financing conveys a signal that AI oriented companies are still away from entering winter. Airdoc is a medical image reading company focused on diabetic retinopathy (DR), skin, coronary and lung image reading as well as other body parts’ image reading.

According to a report issued by EO Intelligence (亿欧智库) in June 2018, medical image reading’s tech maturity are varied in different areas, in which chest and DR image reading accuracy and maturity were ranked highest among all types of medical image reading. Major startups in the area include VoxelCloud, InferVision, 12Sigma, Huiyihuiying, Yitu, DeepWise, Airdoc etc.

2018 AI MedImgReading Maturity

According to WHO provided biggest 10 mortal causes trachea, bronchus and lung cancers(TBLC) are the No.4 mortal cause for western Pacific region, and China, as a major part in population components, has the most TBLC patients. The TBLC related medical images including CT, MRI, and X-ray have been accumulated in years and with a large base, which is an ideal study object for deep learning.

As the uneven distribution of healthcare resources and the lack of radiologists in China, medical image reading solutions have great potentials in soothing the imbalanced healthcare resources and reducing the misdiagnosis or missed diagnosis, especially for little-experience radiologists. As the aging issue becoming more and more intense, the demand of healthcare is waiting for a long-term boost, and accordingly, all diagnosis-related services are preparing for a constant or booming growth. Medical image reading solutions, though do not integrate all body parts’ medical image reading, will welcome a future infused with more matured technology and integrated products along with the development.