Application

## 1. Specialized platform for diseases and source innovation of medical big data -- Knowledgeable medical Cloud

The development of disease diagnosis and treatment in China today is highly short of specialized tools for disease types. The more vertical the field, the less available data tools are. As a platform for clinical data carrying in hospitals, the current electronic medical record system is too old in design concept and use, and it is difficult to cope with doctors' rapidly changing demand for data in the field of serious diseases.

For example, when doctors do research, retrospective data is the first step. Due to the limitations of the existing system in data dimension and disease specialization, many doctors still use the original excel method to enter medical records. To break the data down into different topics, such as looking only at correlations between pathologic classifications and drug efficacy, doctors would have to strip out all irrelevant information and then create a table to analyze the useful information. The process, in which doctors collect data on hundreds of patients, takes up to 80 percent of the study cycle and only 20 percent of the actual production.

Under the premise of standardized structure and unified terminology, the knowledgeable medical cloud can meet the accelerating iterative requirements of hospital clinical data. Using the Knowledgeable Medical cloud, doctors can get the desired information for each case according to the input of different fields. Depending on the type of disease, it can also help hospitals realize personalized and standardized data integration, and finally break through the gap between patient health data and diagnosis and treatment data, so as to form a real sense of health and medical big data.

Take the Liberal Medical Cloud form in thoracic Surgery as an example. Its most complex form has more than 2,700 fields. This means that there are more than 2,700 data dimensions that doctors can choose to focus on when using this form. In terms of technology and products, long-term, in-depth demand analysis, communication and cooperation between the team and users are required.

The reason why understanding the medical cloud involves so many dimensions is that in the clinical field, big data and small data are of equal importance. Special data cases are called outliers in statistics because they affect the statistical calculation of big data and are excluded. However, from the perspective of scientific research, a single special case has special significance, which is of great clinical research value for doctors to understand special individuals and develop innovative ideas and methods. Only when patient data is specialized in diseases or even personalized in departments and doctors can we pay attention to both big data and small data.

Secondly, based on the support for the specialization of diseases, the knowledgeable medical cloud can realize the MDT of thousands of medical records from dozens of hospitals and hundreds of doctors. The cross-verification between different departments, different doctors and different medical records forms is complementary, which maximizes the value of MDT from different dimensions.

In addition, the foundation of AI development and long-term optimization requires high-quality, continuous data. Due to the lack of data quality and dimension caused by historical factors, the AI trained by these data is difficult to be applied to clinical practice in terms of accuracy and generality.

Therefore, only by ensuring the professional quality, structured integration, and diverse dimensions of raw data, will it be possible to develop artificial intelligence with authenticity and accuracy in the future. Polyscience Medical Cloud has been deeply laid out in this direction, and will launch intelligent assisted diagnosis platforms for several major specialized diseases through the medical Big Data joint laboratory in cooperation with the Data Science Center of the Chinese Academy of Sciences.

At present, the medical cloud has covered almost all major disease fields, including: tumor, blood, orthopedics, neurology, neurosurgery, psychiatry, respiratory diseases, etc. It has been applied in more than 3,000 clinical departments in more than 400 first-class hospitals nationwide, among which there are more than 1,400 oncology (including hematologic oncology) related departments.

## 2, intelligent voice input, free the hands of doctors -- cloud sound

Yunzhisheng is an artificial intelligence service focused on the Internet of Things. By using machine learning platforms (deep learning, enhanced learning, Bayesian learning), the company has established a leading core technology system in the fields of speech technology, language technology, knowledge computing, big data analysis, etc., which together constitute a complete artificial intelligence technology map of Yunzhiacoustic. At the application level, the three solutions of AI core, AIUI and AI Service support the landing and implementation of the core technology of cloud Zhisheng.

The intelligent medical voice input system is based on the professional high-performance recognition engine for the medical field of the cloud voice, supplemented by Philips handheld peripheral input equipment; Through this peripheral input device, it can perfectly connect with various systems in the hospital, efficiently process a large number of text input through voice, and interact with HIS and PCS systems in the hospital through voice and function keys on the handheld device.

In addition, Yunzhichun has also developed the first voice recognition engine in domestic medical field, which has done a lot of model optimization for the medical database (millions of medical nouns, thousands of hours of corpus accumulation, extremely complex Chinese and English mixed expressions).

In order to achieve accurate recognition, Yunzhichun has also made deep customization for the hospital. The deeply customized medical speech recognition model calculated the key words corpus according to the whole medical record data of different departments and different diseases, providing scene support for more than 40 clinical and medical technology departments.

Especially in neurology, immunology, hematology, general internal medicine and other departments with a large number of patients with difficult and complex diseases, the accuracy of this speech recognition is more than 95% at present, and the speech recognition rate of individual departments is even more than 98%. At the same time, assisted by cloud semantic correction technology, the overall recognition rate is close to 100%.

Voice input not only improves work efficiency, but also effectively avoids copy-paste operation, standardizes medical record input, and increases the safety of medical record input. Currently, this system can effectively save doctors more than 38 percent of their time.

Since the introduction of the medical-oriented overall program, Yunzhisheng has been officially put into use in more than 20 representative large comprehensive Grade A hospitals in central, North, South and west China, including Peking Union Medical College Hospital, Peking University People's Hospital, Xijing Hospital of the Fourth Military Medical University, Shenzhen Hospital of the University of Hong Kong, etc. About 40 more hospitals are in the trial phase.

## 3. Blockchain technology to solve electronic medical record data sharing and security problems -- Ali Health

The concept of blockchain is not complicated. It consists of three main parts: a widely distributed network, a shared account that effectively allows access to identity, and digital transactions.

In healthcare, the main application of blockchain is the preservation of personal medical records, which can be understood as electronic medical records on blockchain. If the medical record is imagined as a ledger, it was originally in the hands of various hospitals, patients do not master, so patients have no way to get their own medical records and history, which will cause a lot of trouble for patients to go to hospital, because the doctor can not know your medical history in detail.

However, if blockchain technology is used for storage, there will be historical data of personal medical treatment, which can be used for medical treatment and health planning. The real owner of this data is the patient himself, rather than a hospital or a third party institution.

On August 17, 2017, Ali Health announced that the pilot project of "medical consortium + blockchain" cooperated with Changzhou City had been landed. According to reports, blockchain technology has been applied in the underlying technical architecture system of Changzhou medical Consortium, and has realized the secure and controllable data interconnection among some local medical institutions.

It is reported that Changzhou Zhenglu Town Health Center is a community hospital, providing basic medical services for a population of 140,000, and receiving about 30,000 patients every month. According to Zhang Zhihong, the president of the hospital, the huge amount of information from each medical institution previously needed to be distributed to the municipal medical institution information platform. But medical institutions do not communicate with each other, and many business demands cannot be realized. In addition, how to ensure the safety of personal health information in circulation and storage is also a difficult problem faced by the original platform.

The use of blockchain technology can well solve the problems of interconnection and information storage security in medical institutions.

Take the experience of hierarchical diagnosis and treatment as an example: Through the analysis of the physical examination report on the blockchain, the high-risk patients with chronic cardiovascular and cerebrovascular diseases can be screened out. About 5% of the patients who need to be referred can be authorized and transferred by the community doctor to the superior hospital through the blockchain, and the doctors in the superior hospital can quickly know the patient's past medical history and physical examination information after being authorized. Patients also do not need to repeat unnecessary secondary basic examination, and enjoy "housekeeper" medical services from doctors at all levels of the medical consortium, realizing early detection and early diagnosis and treatment of "disease prevention".

Ali Health blockchain technology uses old IT equipment and systems to connect information in series, which has lower access cost and higher security than traditional information methods.