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Ambarella’s CV3 AI domain controller SoC series (hereinafter referred to as "AMBA", NASDAQ: AMBA, a semiconductor company specializing in AI vision chips) was awarded the annual automobile product award in the 2022 Electronics Industry Award, and was highly praised in the annual semiconductor product category.

The Electronic Industry Award is sponsored by British @CIE magazine, which aims to recognize the best professionals, products, projects and companies in the entire electronic industry.

In the annual "Electronics Industry Awards" of "Components in Electronics", a well-known British media (magazine/website), Ambarella won the "2022 Product Award" by virtue of CV3 automotive AI domain controller SoC.

Anba’s award-winning CV3 series realizes centralized AI sensing processing (including high-pixel vision processing, millimeter-wave radar, laser radar and ultrasonic radar), multi-sensor deep fusion and regulation and control of autonomous vehicles by integrating multiple sensors on a single chip. As a result, ADAS L2+ to L4 automatic driving systems have a higher level of environmental awareness.

The selection method of "Electronic Industry Award" is to invite experts in the industry to vote online, and add the votes of an independent expert jury to finally get the winner. The award has entered its fifth year and will soon become an important activity in the industry, opening the door for new business opportunities.

About Anba

Anba’s products are widely used in artificial intelligence computer vision, video image processing, video recording and other fields, including video security, advanced driver assistance system (ADAS), electronic rearview mirror, driving recorder, driver and cabin intelligent monitoring, intelligent car unmanned driving and robot application, etc. Anba’s high-performance, low-power AI processor provides ultra-high definition image processing, video compression and powerful neural network processing. It can extract valuable data from high-resolution video and radar information, and it plays an important role in the fields of intelligent perception, sensor fusion and central domain control processing system. For more information, please visit www.ambarella.com.

At present, financial technology has become a new kinetic energy of the economy, and it is one of the indicators to measure the economic development level of various countries. How financial technology can empower high-quality economic development has also become a hot topic of global concern.

On November 5th, the 5th International Financial Science and Technology Forum opened in Wenjiang District, Chengdu. More than 150 top guests from the world’s political, industrial, academic and research circles once again gathered in Chengdu to analyze the new direction, new track, new trend and new path of China’s economic, financial and technological development around the theme of "digital economy enabling high-quality development". The forum will inject financial power into promoting high-quality economic and social development through more than 10 activities.

The Red Star reporter learned that this two-day forum was sponsored by Southwestern University of Finance and Economics, Chengdu Local Financial Supervision Administration and Wenjiang District People’s Government of Chengdu, and hosted by the School of Finance of Southwestern University of Finance and Economics and China Institute of Finance, Southwestern University of Finance and Economics International Joint Laboratory of Financial Technology, and Southwestern University of Finance and Economics Sichuan Key Laboratory of Financial Intelligence and Financial Engineering.

Vision: Financial Technology Helps Digital China Construction

Today, China’s economic strength has achieved a historic leap, and its total economic output ranks second in the world.

High-quality development has become the primary task for China to build a socialist modernized country in an all-round way, and we must persist in putting the focus of economic development on the real economy.

After several rounds of discussions, the participating experts agreed that financial technology, with its characteristics of integration, accuracy, intersection and openness, has become the key to providing financial support, inciting the capital market and technological innovation, effectively serving the development of real economy and digital economy, helping to strengthen advanced manufacturing industry, realizing high-quality economic development and speeding up the construction of a "manufacturing power" and "digital China".

2022 is a year in which China’s digital economy is fully developed. During the "14th Five-Year Plan" period, China’s digital economy turned to a new stage of deepening application, standardizing development, and universal sharing.

Experts attending the meeting said that, based on this background, this forum is held under the new development pattern of digital economy empowerment. Global financial experts jointly review the process of financial technology innovation, discuss the present situation of financial technology development, and look forward to the wonderful prospect of technology in helping financial service entities, preventing financial risks, and building a digital China and a green China, which is of great significance for forming a wider, wider and deeper opening-up pattern.

Four highlights: groundbreaking technology gives birth to new formats

This forum is carefully prepared and boldly innovated on the basis of previous sessions, and this year presents four new points of view.

The first highlight is that a series of pioneering financial technology systems and platforms were released for the first time at the opening ceremony on November 5th, including AI engineering KubeAI platform, Quant Plus quantitative analysis platform, enterprise risk intelligent identification and early warning system, etc. This is the first time that Southwestern University of Finance and Economics has shown the technical "hard power" of financial universities to the industry, which will bring new products, new models and new formats to the financial technology industry and help enterprises to transform digitally.

The second highlight is that the 5th Chengdu August 80 Global Financial Technology Product Design and R&D Competition officially started, and the competition teams of eight top universities in the world gathered in Chengdu again. The competition will further deepen Industry-University-Research’s cooperation, focus on "new finance and economics" talent training, innovate and standardize the contents of the competition, and innovate the talent training methods.

At the same time, at the Digital Economy Empowerment Financial Technology Innovation Forum held on the same day, the founders of financial technology companies such as Bingjian Technology, Daoke DaoCloud and Kuanbang Technology started a dialogue, focusing on the promotion of enterprise credit evaluation by artificial intelligence technology, AI empowerment investment and other topics to explore the new direction of digital economy development.

In addition, on November 6th, a headmaster’s forum will be held, which will be changed from a closed meeting to an open meeting for the first time. Southwestern University of Finance and Economics will set up a platform to invite the principals and deans of 16 mainstream universities in China to discuss and share new modes, new experiences and new methods of talent cultivation in universities.

Red Star Journalist Wu Huayu According to Wenjiang District

Editor Chai Chang

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"Big data" is a data set with a particularly large volume and data categories, and such data sets cannot be captured, managed and processed by traditional database tools. "Big data" first refers to data volumes? Large refers to a large data set, usually in 10TB? However, in practical application, many enterprise users put multiple data sets together, which has formed PB-level data volume; Secondly, it refers to the large variety of data, which comes from a variety of data sources, and the types and formats of data are increasingly rich. It has broken through the previously defined structured data category, including semi-structured and unstructured data. Secondly, the speed of data processing is fast, and the real-time processing of data can be achieved even when the amount of data is huge. The last feature is the high authenticity of data. With the interest of new data sources such as social data, enterprise content, transaction and application data, the limitations of traditional data sources have been broken, and enterprises increasingly need effective information power to ensure their authenticity and security.

Data collection: ETL tools are responsible for extracting data from distributed and heterogeneous data sources, such as relational data and flat data files, into the temporary middle layer, cleaning, converting and integrating them, and finally loading them into data warehouses or data marts, which become the basis of online analysis and data mining.

Access to data: relational database, NOSQL, SQL, etc.

Infrastructure: Cloud storage, distributed file storage, etc.

Data processing: NLP (NaturalLanguageProcessing) is a subject that studies the language problems of human-computer interaction. The key to natural language processing is to make computers "understand" natural language, so natural language processing is also called NLU (NaturalLanguage Understanding), also known as Computational Linguistics. On the one hand, it is a branch of language information processing; on the other hand, it is one of the core topics of artificial intelligence.

Statistics: hypothesis test, significance test, variance analysis, correlation analysis, t-test, variance analysis, chi-square analysis, partial correlation analysis, distance analysis, regression analysis, simple regression analysis, multiple regression analysis, stepwise regression, regression prediction and residual analysis, ridge regression, logistic regression analysis, curve estimation, factor analysis, cluster analysis, principal component analysis, factor analysis, fast clustering method and clustering method

Data mining: Classification, Estimation, Prediction, affinity grouping or association rules, Clustering, Description and Visualization, complex data type mining (Text, Web, graphics, video, audio, etc.)

Prediction: prediction model, machine learning, modeling and simulation.

Results: Cloud computing, tag cloud, diagram, etc.

To understand the concept of big data, we should first start with "big", which refers to the data scale. Big data generally refers to the amount of data above 10TB(1TB=1024GB). Big data is different from massive data in the past, and its basic characteristics can be summarized by four V’s (Vol-ume, Variety, Value and Veloc-ity), namely, large volume, diversity, low value density and high speed.

First, the data volume is huge. From TB level to PB level.

Secondly, there are many types of data, such as weblogs, videos, pictures, geographical location information, and so on.

Third, the value density is low. Take video as an example. During continuous monitoring, the data that may be useful is only one or two seconds.

Fourthly, the processing speed is fast. 1 second law. This last point is also fundamentally different from the traditional data mining technology. Internet of Things, cloud computing, mobile Internet, Internet of Vehicles, mobile phones, tablets, PCs, and various sensors all over the globe are all data sources or ways of carrying them.

Of course, this is not all the expenses that Zhu Ting needs to deduct. Zhu Ting also needs to pay 1.5%-3% of the agent fees and some miscellaneous expenses of the players’ union. Moreover, because of the talent cultivation, Zhu Ting also needs to pay part of the salary to the Henan mother team. After a full calculation, Zhu Ting’s 1.2 million euros will actually be deducted by nearly 50%, which means that Zhu Ting actually gets 600,000 euros (equivalent to about RMB 4.2 million). But now Zhu Ting obviously doesn’t care about this. To tell the truth, if she wants to make money, Zhu Ting will stay in China. Her annual salary is at least over $1 million, and her income is more than that of studying abroad. Moreover, at home, Zhu Ting has more time to attend business activities, which is also a large amount of income. But for 28-year-old Zhu Ting, she deserves her last chance to fight for her dream. Zhu Ting also knows that if she wants to lead the China women’s volleyball team out of the trough, she must become.

As the first world competition in the Paris Olympic Games cycle, China women’s volleyball team finished sixth, and once again missed the championship. Fortunately, our ultimate goal is not this year’s World Championships, but the Olympic Games two years later. Therefore, this World Championships can be regarded as an opportunity to train and test the team, discover and cultivate some players through competitions, and lay a solid foundation for the women’s volleyball team to return to the peak in the future! Through this World Women’s Volleyball Championship, four players have played their own value, and they can also lock in a place to stay in the women’s volleyball lineup, while three players may not be able to re-enter the women’s volleyball national team in the future through this World Championship.

First of all, let’s take a look at the four outstanding players. Li Yingying, as the core of the team, will not be mentioned. They are Wang Yun, Diao Linyu, Wang Mengjie and Yang Hanyu! Although Diao Linyu is a veteran in this national team, this world championship is the first one she participated in. Diao Linyu’s performance is also obvious to all, and she completely pushed Ding Xia to the bench. In the future, with the latter gradually fading out of the national team, Diao Linyu is definitely the first choice for the second pass position. Wang Yun’s words can be regarded as the biggest discovery of China women’s volleyball team. After that, even if Zhu Ting and Zhang Changning come back, she can still lock in the position of the fourth main attack of women’s volleyball team.

Last year’s Tokyo Olympic Games had a great influence on Wang Mengjie, and she was almost retired by fans. Fortunately, she persisted in the end, and seized the opportunity again at this year’s World Championships, becoming the first free agent of the women’s volleyball team again! Although young Yang Hanyu didn’t get as many opportunities as the previous three players in the World Championships, she was basically replaced when the team was in the most difficult time. However, even though there are few opportunities, Yang Hanyu has grasped them well, at least during his playing time, and has a very good performance. Coupled with the lack of strength and performance of Wang Yuanyuan, the starting assistant attacker, Yang Hanyu is likely to replace Wang Yuanyuan in future competitions, and become a candidate for the main assistant attacker of the women’s volleyball team.

After this World Championships, the three players who are likely to leave the national women’s volleyball team, perhaps including the aforementioned Wang Yuanyuan, can only "abuse vegetables". Once she meets an opponent who is stronger than herself, it is difficult to play. The other two players are Jin Ye, a major player, and Wang Weiyi, a free agent. These two players have one thing in common: they are not young. Jin Ye, 26, and Wang Weiyi, 27, can’t be used as future training objects of the team. Besides, they didn’t play very well in this World Championships, and their strength is far from the level of playing the World Series. They should leave their positions to younger and more potential players!

In order to improve the efficiency of imaging examination and better serve patients, the imaging department of Guzhen County People’s Hospital introduced artificial intelligence AI imaging diagnosis system to assist imaging doctors to provide faster and more accurate examination and diagnosis for the majority of patients.

Recently, the medical imaging department of Guzhen County People’s Hospital has introduced the world’s advanced artificial intelligence (AI) aided diagnosis system (pulmonary nodules, rib fractures, coronary arteries, head and neck vessels, stroke), which means that doctors have joined hands with "AI", and the medical imaging department has officially entered the era of intelligent medical care, providing more accurate, fast and efficient imaging diagnosis for the majority of patients, so that more patients can get timely diagnosis and treatment at an early stage.

AI artificial intelligence, leaving pulmonary nodules nowhere to hide

Early detection and treatment of lung cancer can greatly improve the quality of life and survival rate of patients. As the manifestation of early lung cancer, regular screening of pulmonary nodules is particularly important. Chest CT is the first choice for early screening of lung cancer. A chest CT examination will produce at least 400 CT images, which are great pressure and challenge to doctors’ eyesight, physical strength and endurance. However, naked eye screening is hard to avoid, especially for small pulmonary nodules close to blood vessels, which are prone to missed diagnosis. AI-aided diagnosis system for pulmonary nodules effectively solves this problem. It adopts advanced adaptive network technology and rule algorithm, and incorporates the deep learning and expert experience of a large number of selected cases. It can "carpet screen" every image scanned by chest CT in about 5 seconds, automatically mark suspicious parts, automatically detect the density, size and other related information of nodules, accurately locate the location of nodules and judge the types of nodules. It is highly sensitive and specific for the diagnosis of various pulmonary nodules, greatly improving the detection rate of tiny lesions, and generating a detection guide with one click.

AI artificial intelligence, automatic analysis of cerebral hemorrhage

AI artificial intelligence, sharp eyes detect small aneurysms

At present, the intelligent diagnosis of brain diseases includes cerebral hemorrhage, cerebral atherosclerosis, intracranial aneurysm and carotid vulnerable plaque evaluation. Intracerebral hemorrhage is a refractory disease with high mortality and disability rate in neurosurgery. AI+ head CT, based on machine vision and deep learning technology, bleeding volume, to determine whether there is cerebral hernia.

AI artificial intelligence, hidden fracture is no longer hidden.

AI can have a very high detection rate of rib fractures, especially occult fractures, based on chest CT data, and can accurately mark the accurate location and fracture type interpretation of rib fractures in patients with chest trauma.

AI artificial intelligence helps standardize the diagnosis and treatment of coronary heart disease

Artificial intelligence-assisted coronary CTA has high accuracy and sensitivity. It can automatically identify blood vessels, complete the identification of blood vessel segments, and at the same time, automatically complete the assessment of vascular stenosis and plaque properties, provide suggestions for plaque risk, improve the diagnostic efficiency, and promote the standardization of diagnosis and treatment of coronary heart disease.

At the same time, in order to actively integrate into the Yangtze River Delta integration and develop medical and health work with high quality, improve the professional quality of medical staff and facilitate residents’ medical treatment in Guzhen, Guzhen County People’s Hospital and Huashan Hospital affiliated to Fudan University in Shanghai set up Guzhen Sub-center of Chen Xingrong Imaging Consultation Center of Huashan Hospital affiliated to Fudan University, and carried out online and offline face-to-face consultation and remote consultation, opening a one-stop mode from medical treatment, examination, screening, diagnosis to treatment, so that smart medical treatment can enter ordinary people’s lives and empower medical efficiency. Let many patients relieve their troubles.

The word "big data" has appeared 14 times in the draft of the 14th Five-Year Plan. It can be seen that, as an important vane of national economic and social development, the 14th Five-Year Plan has still made important arrangements for the development of big data, and the guidance for the development of big data in the plan has been integrated into all chapters. Big data is no longer an emerging technology industry, but is becoming an element, resource, motive force and concept integrated into various fields of economic and social development.

The 14th Five-Year Big Data Industry Development Plan issued by the Ministry of Industry and Information Technology at the end of 2021 further points out that by 2025, the estimated scale of China’s big data industry will exceed 3 trillion yuan, and a modern big data industry system with strong innovation, high added value and self-control will basically take shape.

Up to now, the domestic ecological space big data is still in a relatively blank state, and the digital industry based on ecological space is still in an undeveloped field, and only has small-scale applications in agriculture and water conservancy.

According to the data provided by IBM Business Value Research Institute, the total scale of ecological space in China is over 800 million hectares, of which the environmental data gap is over 78%. Moreover, the existing technical means are mostly low-frequency data monitoring and display, lacking in-depth and cross-industry data statistics and comprehensive learning ability, and unable to deeply process the collected data.

Morrel intelligent technologyCompany Limited (hereinafter referred to as "Morrel Intelligence") is a data service company that provides solutions for "big data in ecological space". Based on ANN (Artificial Neural Network) architecture, the company combines self-developed patent algorithm and uses AGIoT (Internet of Things with General Artificial Intelligence) technology to ensure the completeness of data from collection to analysis and application.

"We collect distributed real-time data through various sensing devices of AGIoT technology, and combine the deep learning algorithm of ANN architecture to fit, analyze, summarize and re-learn the data of various dimensions, thus forming application data units that can face different industries." Yang Li, founder and CEO of Morrel, introduced to 36Kr: "At present, Morrel’s intelligent ecological space big data solution has been widely used in agriculture, water conservancy, fishery, forest fire prevention, disaster prevention, medical treatment, construction, environmental protection and many other industries and application fields."

Artificial intelligence is entering a new stage of development. Traditional weak artificial intelligence is also called narrow artificial intelligence, which can only cover a single application field. General artificial intelligence is also considered as strong artificial intelligence, which can realize more comprehensive intelligence and self-awareness. From the perspective of industrial development, at present, it is moving towards the stage of general artificial intelligence.

The drive of big data has made a great breakthrough in artificial intelligence. Without data learning, it can make a reasonable response through reasoning, so as to interact with things that have never been seen or learned, and it has developed into a mature system to avoid potential risks.

Intelligently, Morrel believes that ecological space big data can be collected, integrated, stored, analyzed and applied through acoustic sensors, biosensors, chemical sensors, RFD technology, satellite remote sensing, video sensing, optical sensors and manual monitoring, etc. Ecological spatial data are mostly characterized by flow, and real-time continuous observation is particularly important. Only by processing and analyzing these dynamic new data in real time, and combining with the existing historical data, can we dig out useful information, provide scientific decision-making, and have more statistical significance.

The R&D capability of Morel’s intelligent ecological space big data solution comes from the accumulation of Bill Electronics (Bill Laboratories) before, and the core team has been deeply involved in AIoT for more than ten years. With its own equipment, products, data and analysis capabilities, it has formed a closed loop of R&D, a closed loop of products and a closed loop of sales.

Yang Li further introduced: The learning speed of this ecological space big data solution based on neural network and AGIoT is much faster than that of traditional algorithms. Morel Intelligent has both algorithm threshold and moat in application layer and data cycle. We now have five expert teams including water conservancy, environment, agriculture, chemical industry and data. Expert teams in different fields can provide timely information feedback and teach our system to learn and grow.

Morrel’s intelligence has been rooted in the agricultural field for the longest time. According to the introduction, supported by Morrel’s intelligence to provide full growth cycle data, China’s first documentary about rural revitalization, The Melody Ripes, the Till the Fall, has been broadcast on CCTV-17 Agricultural and Rural Channel. Through the real-time monitoring of AGIoT equipment, the study of farmers’ personal planting habits, the formulation of soil improvement programs, the realization of fine planting and scientific management, and finally the goal of reducing pests and diseases, reducing costs and increasing efficiency.

Moreover, based on its own high-frequency analysis of data collection, Morrel Intelligent can provide customers with a product traceability platform of full-cycle data services and third-party certification.

In addition, Morel’s intelligent ecological space big data solution not only provides real-time environmental monitoring for kindergartens, but also intelligent health management for municipal road lighting, and also provides real-time ground detection of satellite solar panel deployment devices for aerospace fields.

There are two ways for Morrel to acquire customers. One is to absorb the resources of local partners or distributors through localized operation, and jointly expand the localized business; Secondly, through the combination of Industry-University-Research, cooperation with higher education institutions, and participation in vocational training and vocational certification, we can promote targeted marketing to the end market.

At present, Morrel Intelligent has more than 500 customers, providing 55 categories, totaling more than a thousand sets of equipment, with valid data exceeding 200GB, analyzable abnormal data exceeding 2TB, and annual contract amount exceeding 10 million.

According to reports, its project has achieved the global coverage of the domestic market, and has been expanding the markets of ASEAN and the European Union through agents, with fruitful results. Affected by the epidemic, Cambodia, Vietnam and Indonesia of ASEAN, Germany and Belgium of the European Union will provide localized solutions by agents after the epidemic eases.

Morrel was founded in 2018, and its core team consists of expert teams who have been deeply involved in artificial intelligence, electric lighting, communication engineering, agriculture and forestry science and technology, natural science and other fields for more than ten years. It is a national high-tech enterprise and a national small and medium-sized science and technology enterprise. At present, it owns 17 intellectual property rights and two invention patents are being applied for. It is reported that Morrel Intelligence is starting a new round of financing. The financing funds will be used for equipment investment and R&D investment, and it is cooperating with industrial funds to build its own specialized and intelligent production factory.

Faced with the aging population and the rising prevalence of various chronic diseases, reasonable and scientific health risk assessment and management are helpful to better control personal and overall medical expenses and protect personal health interests to the greatest extent.

In recent years, the advantages of retinal image AI in health risk assessment have been shown. What advantages does it have? What value can it bring to the physical examination center and related departments?

At the Frontier Innovation and Wisdom Forum of the 9th 301 Discussion on Health and the 11th Summit Forum of Directors of National Physical Examination Center,Professor Tang Shiqi, deputy director of Health Management Branch of Chinese Medical Association, president of Hubei Health Management Society and academic leader of Health Management Center of Wuhan University People’s Hospital.Make a wonderful share with the title "Retinal Image AI Helps Health Risk Assessment".

In her speech, she pointed out:"Apart from the loss of life, there is nothing more frightening than the loss of vision. It is suggested that fundus photography should be added to chronic disease screening, eye health should be included in chronic disease system, fundus examination should be paid attention to, and the threshold should be moved forward to realize early detection and diagnosis of chronic diseases. "

The transcript of the speech is edited as follows:

Thank you very much for your introduction. The topic I share with you below is "Retinal Image AI Helps Health Risk Assessment". I will share it with you from four aspects, namely, the current situation of fundus diseases, retina as the best health assessment window, assessment of various diseases through retina, and the application of artificial intelligence products of retinal images.

Present situation of fundus diseases

"The 14th Five-Year National Eye Health Plan" listed fundus diseases as the key eye diseases in the next five years for the first time, and proposed early detection, early diagnosis and early treatment to reduce the blindness rate of diseases.

The burden of fundus diseases is heavy. There are more than 40 million patients with fundus diseases in China, and the distribution of medical resources is still uneven. At present, as the most important blinding eye disease in China, the clinical status of fundus diseases can be said to have a long way to go. This is also the main reason why our country has made fundus diseases a new disease in the National Eye Health Plan of the 14th Five-Year Plan released this year.

our countrydiabetesThe prevalence rate has reached 10%~13%, among which the prevalence rate of diabetic retinopathy in diabetic population is as high as 15%~43%. Then the risk of blindness in diabetic patients is 50~80 times greater than that in non-diabetic patients.

hypertensionIt is a common cardiovascular disease. The incidence rate in China is 5.11%, and about 70% of patients have fundus diseases. With the development of the course of the disease, changes such as hemorrhage, hard exudation, lint spots and the like appear in the fundus, and papilledema may occur in severe cases.

Age-related macular degeneration.For those of us over 50 years old, about one in every six people has macular degeneration. Early detection, diagnosis and treatment of macular degeneration are of great significance to protect central vision and prevent blindness. Therefore, it is recommended that people over 50 years old have a routine eye examination every year.

Fundus lesion caused by high myopia.There are about 70 million people with myopia greater than 600 degrees in China. It is recommended to screen the fundus every six months to one year.

Therefore, we should promote the shift from blindness prevention to universal eye health, move the screening threshold forward, and improve the screening of diseases. At the same time, we should pay attention to the early screening of fundus diseases, expand the screening work and avoid irreversible blindness.

It is the best window for retinal health assessment.

There are very important structures in the fundus, including the optic nerve, retina, retinal arteries and veins, macular area, etc., and this is the area examined by the fundus.

Many fundus diseases have no obvious symptoms in the early stage and are difficult to be detected. However, the early stage is often the right time for treatment. Once missed, the lost vision may not be well recovered. 80%~90% of fundus diseases can be screened by taking a photo of fundus.

In addition, medical practice has proved that in addition to ophthalmic diseases, manyCardiovascular, neurological, endocrineOther diseases have obvious or even characteristic changes in the retina.

Evaluation of various diseases through retina

First of all.Diagnosis of diabetic retinopathy by retinal image AI. An SCI article published by Shibei Hospital, Jing ‘an District, Shanghai shows that artificial intelligence has high sensitivity and specificity in detecting sugar webs and proliferative sugar webs (the sensitivity and specificity of detecting sugar webs are 90.79%, 98.5%, AUC=0.946；; The sensitivity and specificity of detecting proliferative sugar net are 91.18%, 98.79%, AUC=0.950). It is feasible to carry out screening of sugar net based on artificial intelligence in community hospital outpatient department.

AI auxiliary diagnosis system for retinal diseases.This article of Zhongshan Eye Center of Sun Yat-sen University was published in the sub-issue of The Lancet, and its SCI impact factor was very high, reaching 24.519. Studies have confirmed that this "comprehensive intelligent diagnosis expert of fundus diseases" developed by Eagle Pupil Airdoc can identify 14 common fundus abnormalities, with an average AUC of 0.955, and it performs well in the screening of various fundus abnormalities.

Retinal image AI to judge ischemic cerebrovascular disease.This is also a paper published in Science Bulletin, a journal sponsored by China Academy of Sciences, with an impact factor of 11.78. The results verified by the team of Peking University Medical School and Tongren Hospital show that (the model) plays a positive role in early detection of high-risk groups of cardiovascular diseases, guiding active intervention, monitoring and evaluating the intervention effect.

The traditional evaluation method of ischemic cerebrovascular disease has many collection indexes, so it needs invasive collection. The blood test takes a certain time, 2~4 hours, so the calculation is complicated and it is difficult to popularize. The new evaluation method based on China’s cardiovascular risk prediction model is retinal image +AI deep learning algorithm, which only needs fundus photography, non-invasive collection, and the detection time is 1 minute, and the report can be made directly in about 1 minute.

Retinal image AI can also evaluate Alzheimer’s disease.The retina is a part of our brain tissue. The degeneration of cranial nerves is also reflected in the subtle changes of retina. Taking CAIDE≥10 copies as the classification standard for high-risk groups (CAIDE dementia risk score is a risk assessment tool for the general population), the retinal AI algorithm is superior to the traditional invasive and complex dementia assessment, that is, it can be assessed by taking retinal photographs.

Retinal AI can also evaluate anemia.Retinal photographs of patients with anemia are usually pale or pale in background, pale in optic disc, and mild edema. The veins are pale. According to the model of retinal artificial intelligence, the AUC of anemia is > 0.9.

Application of retinal artificial intelligence products

Eagle Eye’s products are very good. It has multi-dimensional products and services. First of all, their artificial intelligence auxiliary diagnosis software can screen fundus diseases and lesions, make auxiliary diagnosis and assess the health risk of systemic chronic diseases, and has comprehensive qualifications, including the first three types of ophthalmology certificates in China, including the second, third and CE certificates.

Has excellent performance. The accuracy, specificity and sensitivity are leading in the world, and it is suitable for all mainstream fundus cameras in the market, including Canon and Topcom.

In addition, there is an authoritative endorsement. Carry out the world’s largest real-world research, with the results published in The Lancet magazine; Won the Wu Wenjun Prize twice, the highest award of artificial intelligence in China.

Eagle Airdoc’s fundus camera has the advantages of pupil-free, full-automatic, self-help (no operator required) and no professional darkroom. It is a self-developed domestic camera with high cost performance.

But also provide operational support services. Performance support, training support, follow-up of positive cases, and review by superior medical institutions, the Internet and hospitals.

(For the physical examination center), the retina image AI of Eagle Pupil Airdoc has seven values:

First,Upgrade the ability of eye examination.It can be used for auxiliary diagnosis of fundus diseases and risk assessment of systemic chronic diseases.

Second,Improve the standardization of diagnosis and treatment.It is a registered product, with standardized report, stable state, authenticity and reliability.

Third,Increase the efficiency of effective physical examination centers.

Fourth,Improve academic ability.It can quantify and multi-dimensionally empower scientific research, and artificial intelligence can improve the probability of project application, and expand clinical research opportunities of multi-departments and multi-diseases.

Fifth,Make up for the shortage of ophthalmologists.Automatic shooting, without doctor’s operation, AI-assisted diagnosis of liberation ophthalmologist. Nurses can easily operate it, and it is suitable for in-hospital examination and external examination.

Sixth,It is convenient to check in many occasions.The equipment is small, easy to operate, intelligent and fast, and it can be used in the out-of-home medical examination vehicle, which is suitable for large-scale screening.

Seventh,Historical comparison and continuous management.Realize automatic historical comparison of multiple inspections.

To sum up, apart from the loss of life, there is nothing more frightening than the loss of eyesight. It is suggested that fundus photography should be added to chronic disease screening, eye health should be included in chronic disease system, fundus examination should be paid attention, and the threshold should be moved forward to realize early detection and diagnosis of chronic diseases. A photo of the fundus, early knowledge of the disease.