Wu Enda's latest scientific research results: AI is ready to subvert human doctors

From a biological point of view, the lifeless computer algorithm is not far from us on the day of saving people's lives in times of crisis.

But the premise is that doctors and patients are willing to accept and believe the decisions made by the cold machine.

Recently, a group of Stanford researchers led by Dr. Wu Enda developed a new machine learning model to determine whether patients have arrhythmia through electrocardiogram, and its effect has even exceeded that of human experts.

This new method of automatic diagnosis is of great significance for daily medical care , helping people to make better judgments about even arrhythmia that may be fatal, and prevent it from happening. In addition, it can provide good health care in areas where medical resources are scarce.

Dr. Wu Enda's new achievement is that machine learning is beginning to revolutionize the latest signs in the medical field.

In recent years, scientists have discovered the value of machine learning in the treatment of many intractable diseases, such as breast cancer, skin cancer and eye diseases.

“I am very pleased to see the fact that people can change their minds so quickly and accept that deep learning can make a more accurate diagnosis than some professional physicians in some vertical medical fields.”

Wu Enda said in an email. In addition, he added that it is very exciting to see that researchers have begun to explore the application of medical AI in new fields besides image data represented by electrocardiogram.

After leaving Baidu in March this year, Dr. Wu Enda has returned to Stanford to continue his academic research.

The research team at Stanford University trained a machine learning algorithm to screen a wide variety of irregular heartbeats in ECG data. Some arrhythmias can cause many serious health problems, including cardiac arrest, but these signals are often difficult to capture, and patients have to wear ECG monitors for weeks to ensure safety.

The important and pittled point is that, due to the nature of arrhythmia, it is often difficult for doctors with high medical skills to make judgments about benign and malignant heart rate instability.