In 2017, Chinese artificial intelligence ushered in a true new era.
On March 5, Premier Li Keqiang issued a 2017 government work report, pointing out that it is necessary to accelerate the cultivation and expansion of emerging industries including artificial intelligence. For the first time, "artificial intelligence" was written into the national government work report. Artificial intelligence is also constantly infiltrating into the medical industry, education industry, manufacturing industry and so on.
In the medical industry, as the degree of informatization continues to deepen, the importance of mining, analyzing, and applying big data is becoming increasingly prominent. In terms of quantity, more than 80% of medical data comes from medical imaging data, and medical images have “4V (volume quantity, variety diversity, velocity speed, veracity authenticity)â€, where diversity refers to multimodal images, pathology, There are a wide variety of data such as tests, genes and follow-up information. It is necessary to rely on the support and calculation of new IT to ensure the digitization of images and the authenticity of structured data after reporting.
When medical images encounter artificial intelligence, from policy dividends to technological innovation dividends, the medical industry will usher in more opportunities and challenges. In this regard, Zhao Zilin, chairman of the China Medical Equipment Association and former director of the Financial Department of the Ministry of Health, said: "The application of artificial intelligence in the medical field has experienced everything from surgical robots, medical imaging diagnosis to telemedicine . From small to large, the development of leaps and bounds." Artificial intelligence is not only a subversion of the medical industry, but more innovation. In addition to improving the efficiency of doctors' work, it will also serve as an auxiliary diagnosis, greatly improving the efficiency and accuracy of diagnosis. Precision medicine is possible. Chen Liming, chairman of IBM Greater China, said that IBM is committed to the application of cognitive systems in China's medical industry. After years of medical data mining and analysis, it has achieved high success in the analysis of medical images. In the diagnosis of skin melanoma, artificial intelligence has far exceeded the discriminant of medical experts with an accuracy rate of 97%. At the same time, artificial intelligence supports the provision of such services to thousands of patients at the same time, which can effectively alleviate the problem of “difficult to see a doctor and expensive to see a doctor†in the Chinese medical industry.
Medical imagery "four sides"
The process of medical imaging diagnosis mainly consists of four steps: first, discovery, followed by analysis, third, synthesis, and finally opinion. However, with the uneven medical level in China and the imbalance in the distribution of medical resources, medical imaging is in the realm of “four sides of the songâ€.
· The large hospital is overcrowded, and the doctors who are reading the film are tired of coping, leading to misdiagnosis and missed diagnosis.
The unbalanced distribution of medical resources in China has led to the overcrowding of large hospitals, and the phenomenon of small hospitals has been generated, and there has been a vicious circle.
The number of outpatient visits in the top three hospitals is often tens of thousands. For doctors in clinical departments, a large amount of readings is an arduous task. In this process, we must avoid misdiagnosis and missed diagnosis. This requires a lot of knowledge base and clinical diagnosis experience in the process of reading.
· Primary medical institutions (involving small and medium-sized hospitals and community hospitals) lack doctors who interpret images. Misdiagnosis and missed diagnosis of doctors can lead to tensions between doctors and patients.
The rate of natural misdiagnosis will be higher in primary hospitals due to various conditions, especially those that are easily misdiagnosed.
In clinical diagnosis, doctors mainly rely on imaging diagnosis to determine the type and severity of the disease. In the primary health care institutions, the lack of professional doctors to interpret images has made it impossible to interpret images and to continue medical services. Not only that, because of the lack of professionalism, misdiagnosis and missed diagnosis are major events that directly affect the patient's "life-critical".
· Massive image data has no effective use and becomes a negative asset.
At present, the data of each hospital is like the “island†of information, and the “in-hospital†and “out-of-hospital†data also need to be fully integrated. These are the core issues of big data applications. At present, 95% of medical big data is wasted, because the unavailability of data makes big data not play a good role. The most critical issue for big data to play is the interpretation. "It's not enough to have so much data. I hope to see how to correctly interpret it and let the data guide clinical or personal health.
The essence of big data is to support clinical and scientific research based on data collection. With the complexity and accumulation of data, it cannot form a supporting role and form a negative medical asset.
· The experience accumulated by experts for a long time is difficult to share and pass on.
After five years of graduating, medical students must undergo continuous internships and further studies to become a veritable "expert."
The old experts with thirty or forty years are the "gems" of each hospital, and the non-replicability of clinical medical experience has led to great difficulties in sharing and inheritance.
Based on the current situation of “four-faceted songs†in medical imaging, IBM provides a solution for an integrated cognitive infrastructure platform, introducing artificial intelligence assistance and support for the medical industry, and artificial intelligence will deeply study the application scenarios of medical images. Rely on the advice and experience of industry experts to implement labeling training and simulation and recording of test data, and finally help the doctors and patients to experience better medical procedures through cognitive recognition of medical imaging symptoms.
The artificial intelligence of "the new revolution"
In the whole medical image, medical big data must be image first, use cloud computing to increase connectivity, use deep learning to explore the value of big data, and use the method of sending data to mine the original shallow correlation in more dimensions. The weakly related relationship, using the relationship between the three, greatly improves the therapeutic rate of medical diagnosis and achieves accurate medical care.
In practice, it is found that high-quality, large-scale data accumulation; high-performance computing environment; optimized deep learning method; three resources will be built to build a model of increasing state, and this is the charm of artificial intelligence. IBM can learn and summarize from historical data, quickly interpret the characteristics of the symptoms in the image, assist doctors in the analysis of the disease, and improve the efficiency and accuracy of diagnosis and treatment.
Moreover, in view of the current situation of insufficient primary medical resources, the core of artificial intelligence that can solve the lack of primary medical resources lies in “giving energy†to primary medical institutions and using artificial intelligence to give grassroots doctors the ability to “see the doctorsâ€.
[Case] ​​IBM effectively recognizes the characteristics of medical imaging disorders through cognition
IBM Power Cognitive Solutions helps image interpretation, and IBM can tell doctors how likely it is that patients with this X-ray have a "lung thickening" condition, and doctors can make their own judgments to avoid misdiagnosis, missed diagnosis, and medical care. effectiveness.
Deborah Disanzo, general manager of IBM Global Health, said that in 2015, IBM began to recognize and identify medical images, including cardiovascular diseases and breast images. With hundreds of thousands of patient cases, IBM works with the world's top medical experts to enable artificial intelligence to help doctors interpret illnesses and provide optimal and effective treatment options.
Medical imaging encounters artificial intelligence to make medical treatment more precise
A few days ago, Li Bofu, the big Boss of the innovation workshop and nearly half a billion fans on Weibo, vigorously preached the irreplaceability of artificial intelligence after he recovered. In Kai-Fu Lee's eyes, 50% of humanity's work will be replaced by artificial intelligence in the next 10 years. But at the same time, artificial intelligence will also bring us opportunities, because artificial intelligence can not replace our aesthetics, it will greatly liberate human time, thus liberating human creativity. Regarding the treatment of lymphoma, he said that many doctors at that time did not know its existence. Because medical advances are fast, not every doctor can read a variety of academic journal articles every day to learn the latest treatments. Therefore, in the future, artificial intelligence will be made into a medical assistant, which can better help doctors make judgments and diagnoses.
It can be seen that when medical images encounter artificial intelligence, medical treatment will be more precise. Under the rapid development of computers, information systems, various high-tech testing instruments, Internet medical , Internet hospitals and nowadays artificial intelligence, the management and treatment processes of hospitals and doctors are constantly being re-engineered and changed. The development of technologies, including artificial intelligence, will provide doctors with better tools to enable doctors to diagnose diseases and serve patients more easily, agilely and accurately.
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