Li Yanhong believes that Internet + medical can basically be divided into four levels: O2O services, intelligent consultation, genetic analysis and precision medicine, and new drug research and development.
Li Yanhong introduced Baidu's progress in these four areas:
First of all, in terms of O2O services, Baidu's Baidu doctors now have 500,000 doctors participating in the consultation, and a total of 8 million people have access to relevant medical services through the Baidu doctor platform.
The second level is intelligent consultation. Baidu doctors have also done some tests on the smart consultations we recently launched. For example, we have done a test at Peking University International Hospital. In 80% of cases, Baidu doctor’s diagnosis and Peking University International The doctor's diagnosis in the hospital is consistent, and its accuracy has improved very quickly. And it may perform better in some rare cases, such as the same symptom, 99.99% is a disease, but there may be one in ten thousand, or even one in 100,000 is another rare disease In this case, as a computer, it can assist the doctor to make some corresponding judgments.
The third level is genetic analysis and precision medicine, which is the most exciting direction for doing computer science in these years. Because we speak Moore's Law in the IT field, the only thing outside the IT field that meets Moore's Law is the cost of gene sequencing, so there is a possibility that something revolutionary will continue to emerge in this area.
The fourth level is the development of new drugs. In this regard, some startup companies in the United States, such as atomwise, are already doing this. Baidu believes that computer science and artificial intelligence can help in this regard.
The following is a speech by Li Yanhong:
Good morning everyone, I said in yesterday’s speech that in the era of artificial intelligence, we need to re-imagine every industry. Today I try to re-imagine the medical industry from the perspective of the Internet.
Today's guests come mainly from two fields, one is the Internet field and the other is the medical health field. As I often say in the company, people in two different fields need to repair from the other end to the middle like a bridge. If the goals are the same, the bridge will pass if it is in the middle. If it is Everyone imagines that it is different. If you don't get it in the middle, you will fail. So we try to let each side go to the other side. Let's take a look at Baidu's artificial intelligence, what capabilities we already have, and then look at how these capabilities should be applied in the healthcare industry.
The manifestation of artificial intelligence in Baidu is mainly through Baidu brain. There are four main functions of Baidu brain. One is the recognition of speech and speech. Today's speech recognition has reached 97% accuracy, which means that it is in a quiet environment. It has surpassed the hearing level of normal people; image recognition is actually very clear in the medical field. Just like the medical image just mentioned by Director Li Bin, a doctor can only watch tens of thousands of films in his life, but for computers. It is said that watching hundreds of thousands of millions of films may be considered small data; the user's portrait and natural language understanding can be used in many fields in the field of intelligent consultation. For the medical industry, we have a corresponding Baidu medical brain to provide related solutions.
In my opinion, or from the perspective of the Internet, Internet + medical can basically be divided into four levels. We believe that the first level is the O2O service, how to drain users offline, and distribute them to places that are suitable for dealing with user diseases. The second is a smart consultation. Just now, Academician Zhan Qimin also mentioned that, like IBM Watson's diagnosis and treatment of cancer, computers may be able to surpass human doctors in many cases. Baidu also made some attempts at Baidu doctors. The third level we think is genetic analysis and precision medicine. I will talk about it in detail later. The fourth level I think is the development of new drugs. This aspect is not enough in China at present, but I think this is an area where big data and artificial intelligence can really play a decisive role.
First of all, let's look at this O2O service. Baidu's Baidu doctor now has 500,000 doctors participating in the consultation. A total of 8 million people have access to relevant medical services through the Baidu doctor platform.
The second level is the intelligent consultation. I have just mentioned this example of Watson. Baidu doctor has also done some tests on the smart consultation we recently launched. For example, I did a test at Peking University International Hospital. In the case of %, the diagnosis of Baidu doctor is consistent with the doctor's diagnosis at Peking University International Hospital, which means that its accuracy has been improved very quickly. And it may perform better in some rare cases, such as the same symptom, 99.99% is a disease, but there may be one in ten thousand, or even one in 100,000 is another rare disease In this case, as a computer, it can assist the doctor to make some corresponding judgments. These technologies not only require machine learning for a large amount of medical knowledge, but also the ability to understand patient expressions. This is actually the direction of natural language understanding.
The third level is genetic analysis and precision medicine. In fact, this is the most exciting direction for doing computer science in these years. Because we speak Moore's Law in the IT field, the only thing that fits the Moore's Law outside the IT field is the cost of gene sequencing, so we feel that there is a possibility of something revolutionary in this area. At present, the biggest problem with using genes to treat diseases is that most of the diseases caused by known genes are caused by single genes, and most of these diseases are rare diseases, and most common diseases are suspected to be caused by multiple genes. of. The combination of multiple genes, so how can you figure out which genes are caused by a combination of genes, in fact, requires a lot of calculations.
Professor Zhan Qimin had a cooperative project with him during the Concord. He was to genetically sequence the esophageal cancer patients in China and try to find out which genes work together to cause cancer. Once we figure this out, the future will be like genetic editing. These treatments can be used in more common diseases. Some of the current genetic editing applications are rare diseases, such as the US Spark TherapeuTIcs, which can treat rare diseases caused by viruses that cause loss of vision and blindness, but these The disease is too rare. For most diseases, we need to figure out which genes are needed together, and here we need a lot of calculations. When I talked to people in the medical industry, the medical knowledge that we think is very profound is actually very simple in their view, and vice versa. In our opinion, the calculation is very simple. In their view, this is big. Data and artificial intelligence are a bit difficult, so we hope to truly apply the computing power of hundreds of thousands of servers and the most advanced algorithms for deep learning to the medical and health fields.
The fourth level is the development of new drugs. The small molecule compounds known to be able to form drugs today are probably as many as 10 and 33. This is probably because all the atoms in the universe do not add up so much. How can such an amount be combined with the disease-causing protein to treat the disease? How do you know the molecular formulas that are unknown and find effective new drugs? This also requires extremely powerful computing power and the most advanced algorithms. In this regard, some startup companies in the United States, such as atomwise, are already doing this. We also think that computer science and artificial intelligence can help in this regard.
As I said at the beginning, I hope that people from both sides will work together. We use our big data ability and use our inexhaustible computing power. The medical and health field hopes to collect more and more data and propose at least calculations. The increasingly difficult problem in the field, we work together to benefit hundreds of millions of patients.
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