Leading a new era of integrated diagnosis and treatment with “medical + AI” as the core


liu, tempo Date: 2021-07-27 10:06:56 From:ozmca.com
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From July 7th to July 10th, the 2021 World Artificial Intelligence Conference (WAIC) with the theme of “Wisdom Connected World, All Wisdom Becomes a City” was held in Shanghai. Many Turing Award winners, more than 30 CEO-level speakers, dozens of top Chinese and foreign academicians, and more than 200 leading scholars in the global AI field gathered here. Among them, BioMind, a medical artificial intelligence company, has been invited to participate in the World Artificial Intelligence Conference for three consecutive years.

 

At the “Digital Health, Smart Health” Health Summit Forum, the conference discussed topics such as the development of artificial intelligence medical technology, the empowerment of the biomedical industry, and the new medical infrastructure in the context of the post-epidemic situation. In addition, the conference released the results of the evaluation and acceptance of the medical track evaluation and acceptance of the new-generation artificial intelligence industry innovation key tasks of the Ministry of Industry and Information Technology, and BioMind won the commendation.

 

How AI technology empowers China’s medical digital transformation is the focus of this forum. Li Jingjue, CEO of BioMind Greater China, said at the forum that as the new medical infrastructure and the construction of the national major disease control system become more and more complete, medical labor The intelligent future not only empowers the digital transformation of hospitals, but also contributes to the intelligent construction of the national disease control system and public health capabilities.

 

During the 2020 new crown epidemic, medical imaging artificial intelligence companies have gradually landed from the “cloud” and played an important role in artificial intelligence screening of lung disease images. In the post-epidemic era, most medical imaging artificial intelligence products that have emerged at this stage are far from meeting clinical needs, and more application scenarios must be explored. Therefore, only AI products that can achieve precise diagnosis, precise decision-making, and precise treatment of integrated diagnosis and treatment can truly lead the new era of medical artificial intelligence.

 

medical + AI"

 

Li Jingjue believes that only high-quality data can produce high-IQ medical AI.

 

Medical + AI” is the core of the new era of integrated diagnosis and treatment

 

A large number of entrepreneurs have emerged in the medical imaging AI industry in China, and many AI imaging products have been developed in the rapid iteration of algorithms and big data technology. The amount of financing is nearly two hundred.

 

But at the moment when AI image products are blooming everywhere, the crisis will also follow. The advent of the new era of integrated medical artificial intelligence diagnosis and treatment is forcing AI imaging companies to rethink the value of AI imaging products to medical care, and how AI imaging can truly empower medical digital transformation.

 

Shen Nanpeng, the global managing partner of Sequoia Capital, expressed the same judgment in his keynote speech at the opening ceremony of the conference: if you regard “computing power level” and “application scenario”, you can visually regard the two aspects of AI in the field of life. In terms of legs, we can clearly see that the “computing power” leg is very long and strong, and it grows exponentially. The parameter of the largest deep learning model in 2020 is the 100 billion level, and it has reached the trillion level at the beginning of this year. But “under the premise of exponential growth in computing power, there is still much room for improvement in data mining in life segmentation scenarios.”

 

Andre BioMind Greater China CEO Li Jingjue proposed that the core of the new era of integrated medical artificial intelligence diagnosis and treatment is “medical + AI“, that is, driven by clinical needs rather than AI technology. “This core contains two major connotations. One is that AI products need to have a deep understanding of clinical needs and clinical pain points, not only to help imaging doctors assist in diagnosis, but also to help clinical department doctors to assist decision-making and auxiliary treatment; the other is high-quality data from top medical institutions To become the quality assurance of high-quality AI products, high-quality data can produce AI with high IQ.”

 

Only AI products driven by this kernel can realize an integrated solution of precise diagnosis, precise decision-making and precise treatment.

 

During the epidemic, BioMind responded quickly and launched the BioMind artificial intelligence imaging-assisted diagnosis system for acute infectious pneumonia, which was sent to designated hospitals in Hubei and various places as soon as possible, and it was able to perform qualitative diagnosis of new coronary pneumonia, and the diagnosis accuracy rate exceeded 94. %, not just pneumonia screening. In addition, BioMind can also achieve simultaneous analysis of multiple diseases based on CT and MR application scenarios. For example, based on chest CT, it can achieve qualitative diagnosis of new coronary pneumonia, SARS, other viral, bacterial, fungal pneumonia, etc., and auxiliary diagnosis of tuberculosis, lung cancer, pulmonary nodules, emphysema, etc.

 

This is the main goal of Ande Medical Intelligence BioMind in the new era of “medical + AI” diagnosis and treatment integration: not only to help clinicians shorten diagnosis time, improve clinical diagnosis efficiency, and more importantly, based on the qualitative analysis capabilities of multiple diseases The extremely high accuracy rate can provide basic-level clinicians with auxiliary diagnosis and auxiliary decision-making to the greatest extent, truly help graded diagnosis and treatment, realize the sinking of high-quality medical resources, and improve the diagnosis and treatment capabilities of basic-level hospitals.

 

Clinical needs determine the direction of medical AI

 

Aiming at the first connotation of the new era of medical artificial intelligence diagnosis and treatment integration, “in-depth understanding of clinical needs and pain points”, the BioMind R&D team of Ande BioMind has been rooted in the hospital for a long time since its inception, and has in-depth communication and close cooperation with clinical experts. Achieve from the clinic to the clinic.

 

Through in-depth communication, the BioMind team found that a major clinical pain point is that the higher the complexity and the more difficult to diagnose diseases, the more they need the help of AI imaging-assisted diagnosis, especially at the grassroots level.

 

Take intracranial tumors as an example. Intracranial tumors are a general term that includes dozens of brain tumors. The complexity of the disease is high, and the mortality rate in the world is gradually increasing. The primary clinical needs AI image-assisted diagnosis of intracranial tumors, but there are only a handful of domestic companies that research MR intracranial tumors.

 

This is because the imaging of intracranial tumors has the phenomenon of “same disease with different shadows” and “same shadows with different diseases”. Imaging alone cannot make a diagnosis. The patient’s medical history, clinical symptoms, signs, and other related auxiliary examinations must be used as the basis. Judgments based. This has brought great difficulties to the diagnosis of primary clinicians, and the misdiagnosis rate is high. Some clinicians often use pathological examination or needle biopsy after craniotomy to determine what tumor is, but in fact, this requires extremely high technical requirements and is even more difficult for primary clinicians.

 

Due to the dual considerations of the pain points of clinical needs and the difficulty of research and development, the BioMind team of Ande Medical Intelligence chose to conduct research from intracranial tumors first. The research goal is that in addition to screening for disease, AI imaging can also be used for specific qualitative determination, that is, “what kind of intracranial tumor is it?”, to provide doctors with very accurate auxiliary diagnosis, based on different diseases, doctors will choose in time correct treatment methods to improve the prognosis of patients.

 

At the same time, there is still a big demand for clinics: clinical multi-tasking products in a complete form that meet the clinical scene are needed. Many grassroots clinicians look forward to scanning one part at a time, allowing AI imaging to assist in the diagnosis of all diseases that may occur in that part.

 

But in fact, most of the current AI imaging products cut from a single disease in a single part, and are a simple AI model for a single disease. The “single-soldier combat” model can be very limited in efficiency in the field of diagnosis for grassroots doctors.

 

Based on the above clinical pain points and needs, in June 2018, Ande Medical Intelligence BioMind, in conjunction with Tiantan Hospital, National Neurological Diseases Clinical Medicine Research Center, National Neurological Diseases Quality Control Center, Chinese Stroke Society, and Neurological Disease Artificial Intelligence Center, jointly released the world’s first neuroimaging artificial intelligence-assisted diagnosis product-BioMind.

 

BioMind can identify 27 kinds of intracranial tumors, cerebrovascular malformations, aneurysms, cerebral small vessel disease, ischemic stroke, cerebral hemorrhage, brain trauma, ischemic penumbra, and atherosclerosis through CT and MR images. There are more than 60 kinds of brain diseases such as arterial stenosis. The diagnosis accuracy rate exceeds 90%, and the diagnosis accuracy rate of some diseases exceeds 96%. It helps doctors quickly diagnose and improve their diagnosis and treatment capabilities.

 

High-quality data determines the height of medical AI

Medical clinical diagnosis does not only rely on single-dimensional data. AI imaging products on the market that are only grown by learning image data are still far from being “accurate.”

 

Aiming at the second connotation of the new era of integrated medical artificial intelligence diagnosis and treatment, “high-quality data from top medical institutions becomes the quality assurance of high-quality AI products, and high-quality data can give birth to high-IQ AI”, as early as December 2017, Ande BioMind and Beijing Tiantan Hospital jointly established the “Neurological Disease Artificial Intelligence Research Center” to carry out comprehensive and in-depth cooperation.

 

At the same time, BioMind has also established close strategic partnerships with top scientific research and medical institutions such as the Massachusetts Institute of Technology (MIT) Artificial Intelligence Laboratory and the National University of Singapore.

 

Li Jingjue said, “The combination of multi-dimensional data of top hospitals’ medical record data + imaging data + pathological data is high-quality data.”

 

With AI technology alone without high-quality data, there have been cases of failure abroad. IBM Watson Health and Google Health, which were once considered to be the pioneers of medical AI, both failed due to data acquisition problems. Watson Health was unable to obtain high-quality data in the later stage, due to the high error rate. In 2016, Google’s research institution DeepMind cooperated with three British hospitals to obtain 1.6 million patient medical data, and then was investigated for illegal acquisition and use of data.

 

Through scientific research cooperation with Tiantan Hospital, BioMind uses deep learning algorithm models to systematically train millions of imaging cases in the past ten years, integrating the clinical experience of top hospital experts. While using high-quality data from top hospitals, in order to ensure the security of the data, Ande BioMind sends a research and development team to work in the hospital, so that all training data is not discharged from the hospital, and the cleaned and desensitized data training is all in the hospital. The intranet is completed.

 

In addition, the core technical team of Ande Medical Intelligence BioMind comes from the National University of Singapore, Harvard University, Massachusetts Institute of Technology, Tsinghua University, Chinese Academy of Sciences and other world-class universities. The blessing of a strong team is the technical level of Ande Medical Intelligence’s products that provides a strong guarantee.

 

High-quality data and a strong technical team have become the source of continuous innovation of Ande Medical Intelligence. The solid product strength has helped Ande Medical Intelligence to successfully open the international market. In 2018, Ande Medical Intelligence obtained product certifications from more than a dozen countries including the European Union CE, Singapore, etc., and the products were sold to Germany, Poland, Luxembourg, Singapore, etc.

 

Application scenarios determine the future of medical AI

 

Li Jingjue said at the forum that the value of medical AI lies in solving clinical needs. In recent years, many companies have failed on this track precisely because they did not really understand the market demand and only did what they wanted to do. “If AI products cannot be fully embedded in medical scenarios, products that only improve efficiency are software tools, not real artificial intelligence.”

 

Most AI image products on the market exist in immature software forms, and the algorithm model is still in the training and optimization stage, and large-scale applications have not been completed.

 

In July 2020, BioMind, as one of the joint member units of the international project, became the only target of the national-level medical artificial intelligence public platform project of the Ministry of Industry and Information Technology of the People’s Republic of China-“A public service platform for artificial intelligence assisted diagnosis in the medical and health industry” , The winning bid amount reached 168 million Yuan.

 

At present, BioMind has gradually realized the application of accurate auxiliary diagnosis and auxiliary decision-making covering multiple parts of the body, such as the head, neck, heart, blood vessels, and breast. Before 2023, Ande Medical Intelligence will complete the whole-body system imaging AI-assisted diagnosis and a comprehensive layout of decision-making aid products for multiple diseases.

 

But Ande Medical Intelligence is not satisfied with this. Li Jingjue said that Ande BioMind is gradually deepening from auxiliary diagnosis to precise diagnosis, precise decision-making and precise treatment, trying to create an AI precision diagnosis and treatment integrated system that is more needed by grassroots clinics to help the development of grassroots hospitals.

 

For example, the BioMind cerebrovascular disease clinical diagnosis and treatment auxiliary decision-making system (“Cerebrovascular Disease CDSS”) developed by Ande Medical Intelligence BioMind, assists doctors in the whole process of screening-diagnosis-treatment-prognosis, and helps doctors to achieve from the patient’s admission to the hospital.

 

Li Jingjue believes that artificial intelligence is most likely to bring the technology of top hospitals to the grassroots level and improve the level of diagnosis and treatment of grassroots doctors. Ande Medical Intelligence BioMind has been providing global solutions that support the comprehensive improvement of imaging and clinical capabilities. In the future, it will continue to base itself on medical and in-depth algorithms to provide imaging doctors and clinicians with integrated diagnosis and treatment intelligent solutions that are more suitable for clinical application scenarios.

 

Disclaimer: The market is risky, so choose carefully! This article is for reference only, not as a basis for trading.

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