AI + Medical Diagnoses = More Efficient Healthcare

Ever since the world witnessed AlphaGo beat Lee Sedol, people have become quite familiar with the term “artificial intelligence”.

But aside from the ancient game of Go, artificial intelligence has developed rapidly through the years, and applied in various industries, the medical field being one of the most important areas.

The use of advanced technologies such as artificial intelligence, machine learning and big data in the field of health care is not without controversy.

On one hand, some people enthusiastically believe that the use of these new technologies in the medical field can save lives, lead to new medical breakthroughs, provide patients with a variety of personalized treatment options.

On the other hand, there are many skeptics who are uneasy about potential personal privacy issues, worrying that their case information would be inadvertently mishandled or compromised.

Nonetheless, the combination of medical care and artificial intelligence is an irreversible trend, and their union can lead to increased medical efficiencies and more accurate diagnostic results.

In 1972, Tim De Dombal and Susan Clamp developed AAPhelp, a clinical decision support system, to calculate the cause of disease based on the patient’s condition. In 1974, the diagnostic accuracy of the system had exceeded that of an experienced doctor.

However, the fatal flaw of AAPhelp was its calculation time. It essentially needed an entire night to calculate diagnostic results. For clinical applications, this was simply too inefficient.

Along with the advent of artificial intelligence, computing speeds of machines have since increased exponentially. Now 10 minutes is all it takes to be able to accurately diagnose a rare leukemia, and establish a treatment program.

At the same time, in China, a leading medical artificial intelligence team Airdoc has been carrying out in-depth research in medical diagnoses.

Airdoc has been using medical image recognition and the application of medical big data, along with medical expert guidance, to build a medical diagnostic system.

Airdoc is trusted by many leading healthcare organizations for its stringent data protection measures, expertise, experience and in-depth research in AI.

Currently Airdoc is working with dozens of the world’s leading medical institutions, including Johns Hopkins Hospital in Baltimore, and Peking Union Medical College Hospital in Beijing, in the field of artificial intelligence medical testing and has achieved successful results which are featured in several high profile medical publications.

At present, the Airdoc team is working hard to ensure that artificial intelligence medical testing can be applied in clinical practice to assist doctors to improve the efficiency of medical diagnoses, and overall hospital operating efficiencies.