In recent years, artificial intelligence has been fired so hot, but everyone has been talking about drones and smart homes, but in these mirages forgetting that they are actually difficult to land in a short time, and ignoring smart healthcare, which has already landed in the era of big data.
Now, big data has been applied to smart healthcare, namely to make it easier for patients to seek medical treatment, more efficient diagnosis of diseases, and more accurate medical information. Faster and also more accurate multi-point landing in the medical industry.
Big Data + Medical Development Status
Currently, the domestic smart medical technology is relatively mature, there are a number of tertiary hospitals to introduce "artificial intelligence-assisted diagnostic system", the intelligent system to the image of a robot doctor in front of the crowd, through the fixed-format questions and patients interact with the description of the symptoms of the issued After the results of the examination, the system will automatically issue a diagnostic conclusion, and the first-line clinicians will confirm the conclusion.
According to Xiaozhijun, the robot had PK with more than 200 medical experts in China last week and gained a clear advantage in timeliness. Staff input 100 patient data to the robot, the scene connected to the Tianhe supercomputer, 4.8 seconds to complete. Surprisingly, the robot's diagnosis reached a 100% match with the doctor's original diagnosis.
Back in March of this year, Google's artificial intelligence has achieved extraordinary results in the medical field. Google partnered with Verily to develop an AI algorithm that could be used to diagnose breast cancer, and PKed that AI against medical experts to analyze 130 breast cancer slices to find the tumors in them.
The AI beat the humans in this program. The human medical expert spent 30 hours analyzing the 130 slices to give a diagnosis, and the final result was that the expert was 73.3 percent accurate. The AI, on the other hand, took a fraction of the time to give a diagnosis, with an accuracy rate of 88.5 percent, 15.2 percent ahead of humans.
Three issues of medical AI in the era of big data
First, the era of big data needs to change the way of recognizing and dealing with diseases:
Modern medical treatment is based on the patient's history, symptoms, signs, and laboratory diagnosis, but often ignores the patient's genetic background, genomic data, environmental background factors, and the continuous observation of the main monitoring indicators of disease and subgroup analysis. Including the current daily medical diagnosis and treatment is often based on a genetic characterization of the disease, while ignoring the most basic information.
With the accumulation of medical knowledge, specialization, and fragmentation, it is inevitable that we will move towards integration and systematization in the era of big data. More specialized man-machine cooperation to achieve the most comprehensive diagnosis of the patient.
Second, the era of big data to change the entire medical evaluation:
China's reform and opening up in the past 30 years and the accumulation of economic strength, the increase in the allocation of medical resources, the overall accessibility of health care has been continuously improved.
Not only to the medical outcomes themselves, but also to observe the clinical ethos, not only to focus on patient complications and mortality, but also to focus on physician reports, hospital reports, and bill generation. Using data to improve physicians' ability to self-learn to improve clinical practice is a hint of what big data has given us.
Third, the era of big data needs to change the concept of training medical students:
The traditional medical model has formed a new system in the era of big data, and the specialty training in the past has made doctors more and more limited in their understanding of data. We need to transition from the mere accumulation of physician experience to the accumulation of medical data, which is necessary in the era of big data in medicine, as well as the development of various guidelines in medicine.
As a doctor, we need to change our mindset and embrace the combination of the human brain and the computer, and every future doctor should be skillful in applying intelligent tools to process massive amounts of information in order to seek more accurate diagnostic and treatment options.
Trends in artificial intelligence in medicine
So what should we do next? What are the trends in artificial intelligence?
One, healthcare is at a digital tipping point
The 2017 Internet Trends Report released by Internet Queen Mary Meeker argues that healthcare and healthcare have entered a digital inflection point: the healthcare industry has demonstrated explosive growth in the amount of data input and data accumulation, with 88% of consumers using at least 1 data health tool (telehealth, wearables).
The growth of data has shortened the innovation cycle of medical research and accelerated the clinical trial cycle of drugs on the one hand, while improving the accuracy of diagnosis and the precision of treatment on the other.
Two, data is the key to development
Data is the key to the development of the "medical + artificial intelligence" industry. Xiaozhijun believes that the key to the combination of medical and artificial intelligence is "algorithm + effective data". Advanced algorithms improve data processing efficiency and recognition accuracy, while effective data is the basis for the application of advanced algorithms.
At present, the development of deep learning and other algorithms has been relatively mature, the medical number of "quantity" and "quality" is the main reason to hinder the development of AI applications in the medical industry.
Three, intelligent diagnosis and medical image recognition is more mature
Intelligent diagnosis and medical image recognition is "artificial intelligence + medical" development is relatively mature in two areas.
At present, the relatively mature areas of development include "intelligent diagnosis" and "medical image recognition", and the development of the two areas will enhance the "outpatient" and "imaging department" respectively. The development of these two fields will enhance the supply of medical resources in the "outpatient" and "imaging" departments respectively, and solve the current severe contradiction between supply and demand in the medical industry.
Small Wisdom Summary
In the medical field, big data has a wide range of applications, including disease prevention, clinical applications, Internet health care and other aspects. It can be said that medical big data is the future development trend in the medical field. At present, in the application of big data in the medical industry, China is still in the primary stage, the government, hospitals and data mining technicians need to *** with efforts to make big data in the medical field.