Airdoc CEO Ray Zhang: 7 Opportunities in AI Medical Health

Airdoc is a leading specialist in the medical AI field. The company’s mission is to make healthcare more efficient by leveraging artificial intelligence and deep learning. Under very specific guidance of medical experts, Airdoc has developed algorithmic model services to help doctors improve diagnostic efficiency and accuracy.

In a recent speech in Beijing, Ray Zhang (张大磊) outlined seven opportunities for artificial intelligence in the field of medical health.

Auxiliary medical diagnostics systems and other medical services, which can be used in early screening, diagnosis, rehabilitation, and surgical risk assessment scenarios;
Data digitization, allows for faster access and analysis which can subsequently increase hospitals’ operational efficiencies.
Medical image recognition can help doctors more efficiently and accurately analyze patients’ images;
Medical big data allow medical institutions to better visualize data and leverage the value of the data;
Pharmaceutical drug research and development can leverage AI to reduce the high cost of drug development;
Health and fitness management. Data collected from wearable devices can be used to monitor users’ personal health and to predict and warn for disease risks;
Gene sequencing. Deep learning can facilitate the analysis of genetic data to improve effectiveness of medical care.

Zhang shared about Airdoc team’s work of deep learning in the field of medical image recognition. Through the integration of artificial intelligence in the healthcare industry, Airdoc has established partnerships with a number of top medical institutions in China and overseas, including Peking Union Medical College Hospital (北京协和医院), and John Hopkins Hospital in the US. Airdoc has successfully achieved breakthroughs in the areas of prediction, early detection and warning for cancer, cardiovascular, elderly diseases and other diseases. Airdoc’s auxiliary diagnoses have met or exceeded the standards of top experts, gaining high praise from medical experts and academics.

Zhang said, “Airdoc is merely a clinician’s able assistant, but disease diagnoses encompass many additional social and cultural factors. Airdoc can be seen as an intelligent stethoscope, microscope, sphygmomanometer; a doctor’s tool, which cannot replace the doctor. The final diagnosis must still be made by the doctor. Doctors have been treating patients for millennia, and will continue to, but with technologically more advanced tools.”

Although artificial intelligence has become a global buzzword, there still exist many challenges to creating practical and impactful AI applications. Zhang mentioned six major challenges for artificial intelligence in the field of health care.

First, there is data quality. The data used in machine learning is actually the teaching material for the learning model. The quality of the teaching material ultimately determines the outcome of the study. How to obtain high quality teaching material is a common problem faced by most artificial intelligence medical enterprises. The quality of clinical data is not always reliable.

Secondly, there are patients’ privacy issues. Prior to model training and data preprocessing, patient privacy requires the utmost discretion. Airdoc strictly adheres to the US Health Insurance Portability and Accountability Act (HIPAA) regarding health information privacy, and is also advocating HIPAA’s information protection bill to Chinese authorities.

Thirdly, social acceptance. As society has long since been used to more traditional medical treatment methodologies, the process of fully accepting the integration of artificial intelligence into medicine and healthcare is likely longer than imagined.

Then, the regulatory issues. At present, China’s regulations around monitoring the use of artificial intelligence for health-related big data is still behind those of the United Kingdom and Australia and other countries.

A few more points from Zhang include cross-organizational data model validation, and payment issues. “There are still a lot of challenges in the field of artificial intelligence, we hope to work together with more people who are interested in changing health care to overcome human disease and improving everyone’s health.” Zhang said in closing.