Reborn Technology Upstart

Ye Zishu looked at Pei Qing's puzzled face. It seems that she is still quite unfamiliar with artificial intelligence, especially for someone like her who is not a software and computer major, it is indeed a bit difficult to understand.

This made Ye Zishu consider whether to entrust the task to Phoenix Technology Company, but Phoenix Technology Company is very unfamiliar with medicine and the medical field.

When recruiting at the beginning, they were all concentrated in the fields of industry, software and computer, and the recruitment of talents in medicine and medicine was almost zero.

Moreover, if you want to understand medicine and medical treatment, it is not for fresh graduates to do it. Otherwise, why does it take 5 years for an undergraduate major in medicine, and it is only an introduction to a doctorate.

It is because medicine is too difficult, and it is impossible for Phoenix Technology to maintain a large medical professional team, not to mention the medical team that has left the front line will soon fall behind.

Therefore, software development in the medical field can only be done by Taiji Group itself. At most, it will transfer personnel from Phoenix Technology to take on the actual software development work.

"Normal enterprise management software can be purchased from software companies under Phoenix Technology. They have a lot of mature software systems, and you should gradually switch to information management in terms of management.

However, in the field of medical professional software, if you want to develop it, you can only rely on your own strength, because medical treatment itself is very professional and complicated, and it is not easy for a layman like Phoenix Technology to enter.

As for how to use software technology and artificial intelligence technology to improve the level of medical management, the efficiency of medical research and development, and the analysis accuracy of high-end medical devices, they are all topics worthy of study.

In the field of medical management, using information technology and artificial intelligence technology, an automatic dispensing system can be developed, which can greatly reduce the workload of doctors and reduce the error rate of doctors.

The specific method is to conduct comprehensive data analysis of all medical equipment inspection information, find out possible diseases, calculate the proportion probability of various diseases, and provide medical advice.

The on-site medical personnel can conduct further inspection and confirmation according to the medical plan, and further check the wrong options, which is of great benefit to improving the correct judgment of medical diseases.

The construction of your hospital is relatively late. Even if you spend a lot of money to invite many famous experts and scholars to come here, it will not happen overnight if you want to expand rapidly.

But with this intelligent medical diagnosis system, you can hand over a lot of work to doctors who have just graduated. Only experienced experts are needed for the treatment of major diseases.

Of course, in order to improve the accuracy of this system to a certain level, it needs the support of many high-precision diagnostic equipment. At the same time, these equipment also need to provide automatic data aggregation function to reduce the time of disease diagnosis.

It can even be combined with intelligent image analysis technology to realize online disease diagnosis. If it can be combined with intelligent small detection equipment, the accuracy of online disease diagnosis will be further improved.

However, the latter is more difficult, and ordinary families will not be equipped with special home diagnostic equipment, because even if it is cheap, it will not be very cheap, and it will be a big burden for ordinary families.

But the former solution is completely feasible, especially for diseases with obvious symptoms outside the body, it has a high accuracy of online diagnosis, and can provide remote online medical services to remote areas. "Leaf Book said.

Pei Qing was shocked when she heard Ye Zishu's application of information technology and artificial intelligence technology in the medical field. It turns out that medical treatment can still do this.

"If the accuracy of artificial intelligence's analysis of inspection data reaches a certain level, then the threshold of the medical industry will be greatly reduced, and even self-service medical institutions can be established.

That is to say, the equipment inside is all intelligent and fool-like, and all the inspections are completed by the program itself, and the patient only needs to follow the prompts.

After all the inspection data comes out, big data and artificial intelligence will analyze the data, give a diagnosis result, and provide a treatment plan.

If there is already a mature drug treatment plan, the automatic medicine vending machine can directly prescribe medicine to the patient according to the treatment plan in the hands of the patient.

After returning home, the patient can also be reminded of the time to take the medicine from the smart terminal such as the mobile phone, which can greatly reduce the pressure on the medical system and the treatment cost of the patient.

This kind of self-service medical institution is most useful in the field of physical examination. Because the examination is relatively cheap, people who did not have physical examination all the year round will also choose to do regular examination. "Leaf Book said.

"Is it really as amazing as you said?" Pei Qing still asked in disbelief.

"All of what I said can be done, but in the specific implementation process, you need to have a wealth of clinical diagnosis data. The richer the data, the higher the accuracy of artificial intelligence diagnosis.

Of course, it is also related to the detection accuracy of medical equipment. In this regard, I will provide a lot of technologies, and medical equipment can basically meet the standards required for artificial intelligence diagnosis.

So next, you need to spend a lot of time on sorting out the disease data. Since your hospital has just been established, this kind of data is not rich enough.

You can purchase clinical data from other medical institutions, whether they are domestic or foreign, so don’t be afraid to spend money on this.

After the artificial intelligence medical diagnosis system is initially established, it can be tested in your hospital first, using the method of human-machine cross-diagnosis.

On the one hand, it can further improve the accuracy of artificial intelligence diagnosis, and on the other hand, it can also prevent manual diagnosis errors. Only when a certain standard is reached can we provide limited artificial intelligence independent diagnosis services to the outside world. "Leaf Book said.

"Although after hearing your words, I have a certain degree of confidence in the application of artificial intelligence technology, but relying on our own technical strength, even if we can achieve this, it will be a long time later." Pei Qing said.

Although these words are frustrating, they are true. In three to five years, it is basically impossible for artificial intelligence to diagnose independently.

Medical matters need to be cautious. The diagnostic accuracy rate has not reached more than 99.9%. If you provide services to the outside world casually, once there is a mistake, it will be a huge loss for both the patient and the medical institution.

"You don't want me to help you develop such a system, do you?" Ye Zishu looked at Pei Qing's expression and asked uncertainly.

Hearing his words, Pei Qing immediately said happily: "The boss is still smart. He saw through my little thoughts early in the morning. If he wants to do this as soon as possible, only you can do it."

"But I don't have time!" Ye Zishu said helplessly.

"It's okay, we can wait until you have time, we can make a list of existing diseases first, and collect clinical data of various diseases at the same time." Pei Qing said with a smile.

When Ye Zishu heard this, Pei Qing was completely dependent on her. Did she take too much care of the Taiji Group during this time, causing her to become heavily dependent?

But thinking about it carefully, it seems that I don't care much about Taiji Group as much as other companies. Whether it is Shengshi, Phoenix, Qinglong or Xuanwu, I spend more time than Taiji Group.

I just gave the Taiji Group a few formulas of health products, and basically ignored the rest. Only when I asked for money, would I contact Pei Qing.

Just like the vaccine technology that is going to be given now, it is also because the Kirin Industrial Group already has the protein structure synthesis technology and has the protein industry foundation, so it will pass a technology to the Taiji Group.

I really don't have the idea of ​​building a complete industrial chain specifically for Taiji Group. If I insist, it is medicinal planting technology, but this is not a complete industrial chain.

In fact, what really exerts the effect of Chinese herbal medicines is not the direct use of Chinese herbal medicines to make medicines, but the extraction of effective pharmaceutical ingredients from Chinese herbal medicines.

Then it is mixed with other important active ingredients according to the ratio and special method to make medicines for certain diseases. This link alone is a very huge link.

Because there are tens of millions of diseases in the world, if he wants to do this, it means that he needs to have a treatment plan for all diseases. He thinks it is difficult, and the most he can do is to provide the active ingredient extraction technology of Taiji Group for traditional Chinese medicine.

So when the words of refusal came to his lips, Ye Shu couldn't say anything, but said: "There is some truth in what you say, the necessary software development team still needs to be established.

If you want me to help you develop such a system, you have to wait until I am free. You can't rush me. "

Hearing that he agreed, Pei Qing said happily: "I definitely won't rush you, because collecting and sorting out these clinical data will probably take one or two years and countless money."