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News EO
Jun 15, 2020
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News EO
Jun 15, 2020

Medical AI Tech Shukun Closes Series B1 Funding Round of CNY 200 Million

Chinese medical AI startup Shukun announced that it had closed Series B funding at a deal value of CNY 200 million. This investment was co-led by BOC International and CCB International’s Jianxing Fund, participation came from sequential investors China Creation Ventures (CCV) and Huaigai Capital (HG Capital). Shukun plans to utilize this capital injection to accelerate landing AI technologies in all-tier clinics and community care centers while continuously advancing in the heart disease, neural systems and oncology areas. As a medical solution provider, Shukun provides hospitals with a smart end-to-end workflow, called ‘Scan-to-Report’ – an efficient procedure that allows booking, examination and receipt of reports within the same day. So far, this AI startup has built three comprehensive platforms covering three major human organ areas: heart, brain and chest. Even further, Shukun also launched a community-based medical imaging cloud platform, which significantly benefits citizens by making it more convenient for them to do the physical examination and follow-up checks. Within the three years since its inception, this high-tech medical company has accumulated nearly 100 patents and has been recognized as an ‘Innovative Medical Device’ by the Chinese Food and Drug Administration. Now it eyes an accelerated expansion into more triple-A hospitals nationwide, as it simultaneously seeks commercialization in joint efforts with giants in the field of medical devices, such as GE Healthcare and Philips Healthcare. From a long-term perspective, the in-depth integration of AI technology and medical application is just a start. In the Governmental Two Sessions, not long ago, one representative from a radiology department introduced that it takes from at least 30 minutes to one hour to do the traditional check and diagnosis, including the stages: ‘scan – post-treatment – diagnosis  – initial reporting – report review.’  For patients, they should usually wait for one to three days to receive the reports. This is the area where AI technology should enter. “The lack of medical resources has always been one of the rooted reasons of China’s medical issues,” says Mr. Zhou Wei, the managing partner of China Creation Venture, “the most efficient way is to utilize AI such advanced technologies to assist doctors in solving the imbalance between demand and supply.” Amid the COVID-19 crisis, this startup has extended its service coverage to over 200 hospitals nationwide. It is not the only AI-based medical tech that has embraced a boosting strategy at this particular time. Invervision, the lung cancer detector, launched a deep-learning system in the epicenter of Wuhan to help frontline doctors fight against the deadly virus. In the coming second wave of the epidemic, high-tech tools are a must to shape a possible solution for all mankind.

News EO
Feb 3, 2020
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News EO
Feb 3, 2020

Infervision: Our AI Detects Deadly Coronavirus via CT Lung Screening

Infervision (推想科技) described its coronavirus detection model as working through CT lung screening. This means that the new model detects ground-glass opacities (GGO) in the lung that may later be confirmed as one of the complications of the virus. The firm's model has already been used by Wuhan Tongji Hospital, one of the frontline hospitals that has been fighting with the epidemic in Wuhan. It is set to be deployed in multiple other hospitals in the near future, Infervision said.  “It serves as a surrogate to PCR diagnostic as the lab capacities aren't enough to keep up with the rising number of suspected cases in the afflicted regions," added the company. Another diagnostics solution support for the rising crisis was launched by Shenzhen-based genomics giant BGI Genomics (300676: SH) on January 28. The company's stocks opened around 10% up as the mainland's stock markets open on January 3, 2020. “The new coronavirus may cause infections with no symptoms and sicken otherwise healthy people,” postulated the Lancet, showing how hard it is presently for hospitals in Wuhan, which are racing against time to diagnose large numbers of patients. The new diagnostic solutions possess tremendous importance for the afflicted region, considering the symptoms of the new virus are similar to other fast-spreading diseases like flu, complicating the process and creating excess demand thanks to a large number of concerned patients who need to be assessed. "Symptomatic patients are piling up in the hospital – AI can help triage the patients quickly," said the firm. "Patients have been seen without any noticeable symptoms like fever or cough, but showing large GGOs in the lung," The Beijing-based private firm had long been drawing the attention of wealthy venture capitalists, including Qiming Venture Partners and Sequoia China; it has secured around USD 100 million since its inception in January 2016. The team has been adopting deep learning technology broadly in the medical imaging field. The firm was involved in an early victory in this complex battle: for the first time since the emergence of the new virus in late 2019, the number of new suspected coronavirus cases in China started to drop, over two consecutive days, on December 31 and January 1, 2020 - mostly driven by faster diagnostic solutions. PCR diagnostics had shown that it could play a crucial role. 

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Aug 8, 2019 · tmtpost
Analysis
Jul 27, 2019 · EO Company
Analysis EO
Jul 24, 2019
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Analysis EO
Jul 24, 2019

Infervision Plans AI Tool for Whole Treatment Process of Lung Cancer

Infervision is planning to debut a medical imaging AI solution for the whole treatment process of lung cancer, including prediction, diagnosis, treatment and prognosis, according to Chen Kuan, Infervision’s founder and chief executive officer, disclosing it in a Chinese medical forum on July 20. The new solution has been adopted in two Chinses tertiary hospitals, verifying the feasibility of clinical practice, said Mr. Chen. While most of Chinese AI diagnosis products providers mainly focus on the diagnosis sector, their clients - hospitals - expect for an integrated system to help doctors make decisions in the whole workflow. In the past four years, the Beijing-based startup has employed deep learning algorithms to analyze medical images from DR, CT and MRI, developing AI diagnosis solutions for lung cancer, chest-related disease, stroke, bone disease and breast cancer. To meet the demand of doctors, the company also develops a medical research platform, which becomes the passport for Infervision to build cooperation with hospitals. At present, Infervision is operating in 32 Chinese cities, and another seven countries in regions of North America, Asia and Europe, cooperating with over 300 hospitals worldwide. Its intelligent medical solutions complete more than 38,000 diagnosis per day, according to Mr. Chen. The ten-year survival rate reaches 92% to date for the patients in stage 1 lung cancer - stage 1 lung cancer means that a tumor is discovered, but it is still localized within the lungs. However, only around 4.2% of the patients in stage 4 can be alive after five years since they start treatments. Thus, detecting lung cancer’s risks in the early stage is the key to the successful disease treatment, said Wang Chen, dean of Peking Union Medical College. Chinese government issued a document for the development of the nationwide medical and healthcare careers on July 15, setting a goal that the five-year survival rates of all types of cancer should be above 43.3% in 2022 and 46.6% in 2030. There’s a long way to go obviously. Lung cancer is the targeting disease for most of the Chinses AI diagnosis tools developers, because of the sufficient medical imaging records generated from Chinese lung cancer patients. Both the incidence rate and mortality rate of lung cancer rank the first among all types of cancers, 11.6% and 18.4% respectively in the world. In 2017, more than 100 companies tapped a huge need for lung cancer accurate medical diagnosis, due to a large number of patients in China and a shortage of well-trained doctors able to diagnosis accurately, according to Zou Guowen, partner of Dalton Venture, a Chinses medical-oriented VC institutes. Investors are optimistic about the potential use of AI to recognize cancer, with more than a dozen companies in China raising USD 142 million in venture capital and private equity funding in 2017 and 2018, according to KPMG.  Infervision is regarded as a dark horse in the AI medical area, attracting reputable investors to join the funding game, such as Sequoia Capital China, CDH Investments, Qiming Venture Partners. The total funding of the company in the past four years surpasses CNY 600 million (USD 87.18 million). However, the China Food and Drug Administration (CFDA) upgraded the Medical Device Classification Catalog last August, putting AI products for diagnosis into the list of Class III devices. The companies producing such products have to apply for the Class III device licenses, which can take more than two years to obtain. The AI diagnosis products can't be listed in the hospitals' procurement catalog without the license, resulting in obstacles of commercialization because selling products into hospitals is a mature business in the market. No company received a license to date, according to Cao Luqian, investment manager of Jiangmen, a fast-growing VC company led by the former chief executive officer of Microsoft Accelerator China. The regulatory process is also pricey, costing up to CNY 4 million (USD 581 thousand), said Zhong Xin, chief executive officer of 12 Sigma. “It takes more money and time to get a license and many small companies will find it hard to get their products into the market,” said Mr. Zhong, “It’s not easy for newcomers.”

News EO
Jun 4, 2019
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News EO
Jun 4, 2019

There is a Promise of Hope from China for the Diagnosis of Tuberculosis

Infervision (推想科技), a Chinese MedTech company, revealed intriguing insights on its tuberculosis diagnostic support product at the World Health Assembly in Geneva. The company implied that they are going to launch their product overseas, particularly in tuberculosis-imposed (TB) regions. Infervision provides several solutions including, among others, lung cancer and stroke medical-imaging diagnostics supports for the use of doctors. Amongst its competitors in the same area, Deepwise (深睿医疗), VoxelCloud (体素科技) and Huiyihuiying (汇医慧影), Infervision distinctively focused on lung cancer diagnosis and strives to be a global company. (Find more on Infervision's global expansion in this in-depth coverage)  The company's tuberculosis initiative is a strategic one and may be fruitful in the long term. First, MI diagnosis process is based on the cumulative saturation of the big data, which yields better learning of the machine and results in a more precise AI for the product. Thus, Infervision's expertise in lung cancer imaging and diagnosis presumably facilitates the company's overall operational effectiveness and fruitfulness of the tuberculosis product. Infervision will likely to enjoy the early mover's advantage.  Secondly, tuberculosis is a third-world countries' problem, but a Chinese company could find an advantage to collect data from China and apply its intelligence overseas. In 2018, there were 1,110,659 tuberculosis cases in China, with around 94% success rate of treatment. Indeed, the clinical experience from China can be well implemented in the regions where tuberculosis severely hit. Infervision's team is well-equipped and designed to operate in overseas as a global company.  However, application of such a technology in Africa and SEA is only a sweat dream if contemporary infrastructure capacity of these regions considered. The prerequisite of applying an MI diagnostic software is having a necessary healthcare infrastructure, such as MI and Xray devices. Hence, Infervision's tuberculosis initiative is only a long-term one to be implemented in developing regions. Nevertheless, the company has further approached to provide a complete circle of AI-driven healthcare services and might eventually enjoy being an early mover in the industry. Tuberculosis product shows that Infervision is trying to catch up with Yitu Tech (依图科技) and 12 Sigma (图玛深维) in terms of product diversity, as well.  On December 7, 2018, Infervision completed its Series C, led by CDH Investments(鼎晖投资) and followed by Sequoia China, Haitong Leading Capital Management, Taihe Capital(泰和资本), Advan Tech Capital, Xiang He Capital(襄禾资本) and Genesis Capital. Infervision claimed that its services have been used in around 200 hospitals worldwide and provide daily assistance with approximately 20,000 scans for lung cancer screening: which constitutes the most critical investment indicators for an AI-driven diagnosis assistance provider companies.

Analysis EO
May 13, 2019
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Analysis EO
May 13, 2019

Without CFDA Approval, How Business Run for AI Medical Imaging Diagnosis?

After introduced and explained by Geoffrey Hinton’s paper published in 2006, deep learning algorithm has been applied in improving the accuracy of image recognition by computer scientists these years. In the past of decade, scientists are continually making breakthrough on the image-related technologies, including image recognition, segmentation, character extraction, quantitative analysis and comparative analysis. These advanced technologies has been applied in various industries, especially in the works relying on images originally. Medical imaging diagnosis is a typical one. Medical image, including many types like X-ray, computed tomography (CT), positron emission tomography (PET), magnetic resonance imaging (MRI), etc., is used to diagnose many diseases by doctors today. However, the number of Chinese imaging doctors is in short supply, and there is a shortage of doctors with abundant clinical experience, especially in primary hospitals in towns and villages. In addition, doctors diagnose mainly relying on their experience, so there are lots of misdiagnosis and missed diagnosis. Since 2012, many start-ups have emerged in China, which apply image recognition and other image-related techs in the process of image diagnosis. They hire top-notch artificial intelligence engineers and outstanding imaging doctors to train algorithmic models and develop medical image-assisted diagnostic products. These products can greatly improve diagnostic efficiency and diagnostic accuracy, which are really good assistants for doctors. However, these products are forbidden to commercialize without the certification from CFDA (China Food and Drug Administration). In other words, if require the certification, the products can enter the hospital’s medical suppliers list and can be purchased and reimbursed by national medical insurance fund. Because these AI Medical Imaging Diagnosis Products are newly emerging ones, CFDA does not have mature certification standards, so the assessment progress is really slow. For now, there are only two China’s companies requiring the certifications. So how do these companies run their business and where does income come from? Medical valuation of AI medical imaging diagnosis AI medical imaging diagnosis products emerged in China are mainly for cancers,especially lung cancer and breast cancer. There are a large number of cancer patients in China. More than 10,000 people were diagnosed with cancer every day in 2014, which means that 7 people were diagnosed with cancer every minute, of which lung cancer ranked first, according to the National Cancer Center. In 2017, the number of lung cancer patients reached 800,000, and the deaths were nearly 700,000. And the death units are still growing at a rate of 26.9% per year. It is estimated that there will be 1 million people dying from lung cancer in China in 2025, according to the Capital Medical University. Breast cancer is the most severe malignant tumor among female population. According to the cancer report published by the World Health Organization's International Agency, which contains the research results from 184 countries and regions, the incidence and mortality rate of breast cancer among Chinese women is at a low level in the world, but the morbidity and mortality have increased rapidly in the past 20 years. In addition, the number of Chinese breast cancer patients accounts for 11.19% of the world. According to the National Cancer Center, there were 278,900 new breast cancer patients emerged in 2014, accounting for 16.51% of the incidence of female malignant tumors, which ranks first in the incidence of female malignant tumors. So how many imaging doctors does China have? The answer is only 150 thousand. Besides, more than 50% of imaging doctors work more than 8 hours a day, and 20.6% of them work more than 10 hours a day. The annual growth rate of medical imaging data in China is about 30%, while the annual growth rate of imaging doctors is only 4.1%, according to VCBeat.net, a medical content platform. Under the heavy workload, doctors are probably to make mistake on diagnosis. DeepCare, a Chinese start-up developing related products, made an experiment to analyze the performance between doctors with different working length. In this experiment, a pathologist with 40-year working length and a pathologist with 10-year working length diagnosed the same group of lymphatic metastasis digital pathological sections. The result shows that the disparity of true positive rate (TPR) between these two doctors are as high as 30%. Using AI to help doctors make diagnosis can greatly reduce the workload of doctors and improve the accuracy. For example, InferVsion (推想科技), a China’s start-up developing AI-enabled medical imaging diagnosis solutions, provided its two products, AI-DR and AI-CT, to Tongji Medical College of HUST. These products detected lung cancer from 110,000 X-rays and more than 3,000 CTs, and the detection rate surpassed 92% and 95% respectively with only 5 seconds. Landscape of AI medical imaging diagnosis market So how many companies develops these kind of AI products? According to EO Company, there are 61 typical companies in China, and 41 are founded between 2014 and 2017. Since 2016, investments in China's AI medical enterprise has begun to explode. The number of investments has increased from 10 in 2015 to 22 in 2016, while the investment amount has increased from CNY 162 million (USD 23.75 million) in 2015 to CNY 1291 million (USD 189.25 million) in 2016. The peak of investments occurred in 2017, when there are 35 investment totally in CNY 4.95 billion (USD 0.73 billion). It is said by some investors that there are more than 100 companies developing this kind of products in China, but some companies are not known to the public. Among these 100 companies, 90% of them develop diagnostic products for lung cancer, because the number of cancer patients in China is huge, which means the lung cancer case data is rich. And the algorithm models need a large amount of data for training. Besides, there are abundant papers and academic materials to analyze lung cancer, and the lung cancer’s research is the most mature among various types of cancer. In addition to lung cancer, there are also some products for other diseases, such as diabetes, stroke, breast cancer, esophageal cancer, fractures, skin diseases, liver cancer, prostate cancer, and cardiovascular diseases. Representative companies in this field include inferVision, DeepWise (深睿医疗), 12Sigma (图玛深维), YITU Medical (依图医疗), VoxelCloud (体素科技), United Imaging Healthcare (联影医疗), Airdoc, etc. InferVision was founded in 2015, and it is the top enterprise in this field. It has raised for 5 rounds of financing totally in more than CNY 500 million (USD 73.30 miilion). Its core product namely InferRead CT Lung, which is extremely sensitive to tiny nodules and ground glass nodules. It can help doctors improve diagnostic efficiency by 30%-50% with ensuring accuracy. As of May in 2018, the product has been adopted in more than 150 China’s hospitals, mainly in the first-class hospitals. DeepWise was founded in 2017, a start-up with rapidly development. It has raised 3 rounds of financing within one year since it founded, totally in nearly CNY 300 million (USD 43.98 million). The company's core product is also for cancer diagnosis, and it only takes 30 seconds to make a diagnosis. The accuracy of this product reaches 98.8%, which means its sensitivity and specificity of lung nodule detection have reached the international leading level. As of December 2018, this product has been adopted in nearly 300 China’s hospitals. 12Sigma was founded in 2016, and it has raised 4 rounds of financing totally in about CNY 250 million (USD 26.65 million). Its core product namely is σ-Discover-Lung, which is also for the lung nodule detection and analysis. In addition to leveraged by deep learning algorithm, this product is also improved by the 3D segmentation technology independently developed by 12Sigma. As of June 2018, this product has been adopted to more than 100 China’s first-class hospitals. YITU Medical was founded in 2012, which is a subsidiary of YITU, a China's AI unicorn enterprise. Its core product, Care.Ai TM, is for a variety of diseases, including lung cancer, bone age detection, pediatric intelligent diagnosis, and medical record intelligent search engine. As of January 2019, more than 50 top hospitals in China has adopted this product. However, there are only two China’s companies obtaining the certification from CFDA. Without this certification, products cannot enter the hospital's procurement list. On August 1 of 2018, the new edition of the Catalogue of Medical Devices, which was updated by CFDA, was officially put into effect. Among them, the category of "in vitro diagnostic software" contains the AI medical imaging diagnosis products. According to this category, if the diagnostic software provides diagnostic recommendations through its algorithm with only has the auxiliary diagnostic function - does not directly give the diagnosis conclusion - the related products are managed as the Class II of medical devices. If the software automatically identifies the lesion by its algorithm and provides clear diagnostic prompts, the software’s risk is relatively high, and the related products are managed as the Class III of medical device. The third type of medical device application is more difficult than the second type, in which clinical trials are needed for the third type. Till now, only Landing-Med (兰丁医学) and EDDA Technology (医软信息科技) have obtained CFDA certification, so the two companies have already bid farewell to the free trial stage, and customers can pay them legally. So how do other companies that have not been certified run business? In fact, companies and investors are trying to explore a new business model. At present, these companies earn money by cooperating with doctors in scientific research. Enterprises provide doctors with support for algorithm models, computing sources, data processing and analysis. And companies can obtain a part of the compensation from research funding. Of course, another more important value of scientific research cooperation is to cooperate with hospitals and use the hospital case data to train their algorithm models. Most companies mentioned above are applying for a Class II certificate, but there is no new progress. According to industry investors, although the new edition of the Catalogue of Medical Devices has been in operation for more than half a year, the certification system for AI imaging diagnosis products is still being improved. It is expected that this kind of products will successfully apply for Class II certificates by 2020, and certificated products should be hardware combining with software.

News EO
Apr 21, 2019
News EO
Apr 21, 2019

Infervision’s Stroke Diagnosis Decision Support Product Shines

A stroke occurs when the blood supply to the brain is interrupted or reduced by some reasons. Within minutes, brain cells begin to die, and within hours some parts of the brain may be disabled; thus some significant parts of the body may be disabled permanently or temporarily. In a matter of days, the survival rate is as low as 50%.  Worldwide, stroke leads to the death of around 6 million people every year, and it is attributed to the second leading cause of death and the third leading cause of disability. As the overall economic development level decreases, it kills more people. China is the country where one can see the most stroke originated death; it killed more than 2 million people in China in 2016. By comparison, stroke killed more than 140,000 Americans last year. Computed tomography (CT) is the ultimate method to diagnose the stroke. It can save the precious hours in diagnosing the stroke and progressing the right treatment to it. In stroke treatment and alleviation, every minute is vital. However, only around 61% of the emergency medical service (EMS) providers accurately detects stroke timely. The fail rate is attributed to the general education level of the doctors and technical deficiencies.  Infervision’s (图像科技) “InferRead CT Stroke” software locates the bleeding area on a medical image, measures the bleeding volume thus assisting the doctor for faster and more accurate diagnosis of stroke. Globally, Infervision is not the only company who provides such software. For instance, a product called NuroView detects stroke with as high as 89% accuracy in the USA. However, Infervision is the most significant company in China in dealing with the issue. As of now, Infervision has around 300 cooperative hospitals using its products and software dealing with the Stroke diagnosis.   On December 7, 2018, Infervision closed its series C1 funding led by CDH Investments (鼎晖投资) and followed by Sequoia China, Haitong Leading Capital Management, Taihe Capital(泰和资本), Advan Tech Capital, Xiang He Capital(襄禾资本) and Genesis Capital. CHEN Kuan (陈宽), founder and the CEO of Infervision, dropped out of his PhD program after he realized the opportunity of integrating AI to the healthcare industry in 2015. His company has attracted around CNY 500 million fundings so far from the prestigious investors, such as Sequoia. With a strong market capacity and proper products, together with a well-working managing team, Infervision confidently looks ahead; to the days when China has more than a hundred million people over 80 years old. Then, we all will witness Chen’s grand vision.

News EO
Dec 12, 2018
News EO
Dec 12, 2018

Infervision Completes its 2018's Second Funding Round in 2018

On December 7, 2018, Infervision(推想科技) closed its series C1 funding and the actual amount has not been released yet. This funding round is led by CDH Investments(鼎晖投资) and followed by Sequoia China, Haitong Leading Capital Management, Taihe Capital(泰和资本), Advan Tech Capital, Xiang He Capital(襄禾资本) and Genesis Capital. The raised fund would be used to finance R&D and marketing. In 2017, there are 280 investments in digital healthcare industry, while in 2018, the number has dropped to 148 by far but total funding amount surpasses the number of 2017. Along with the favored "Healthy China 2030" policy published by the State Council in October 2016, investments in healthcare has been heated up and healthcare startups sprang in clusters, whether in pharmaceuticals or in big-data-backed healthcare tech companies. Though investors are more prudent and less risky in general, AI solution and healthcare industries are still chased by capital. In a capital winter for China startups, new funding round secured by Infervision reveals that the company is favored by the capital market for undisputable advantages. Regarding the funding, the Partner of CDH Investment YING Wei(应伟) claimed, “AI product should not march in place at a conceptual level, but needs to prove its capability and applicability. In past three years, Infervision dedicated in both R&D and landing AI tech. Embedded in clinical scenarios, Infervision concentrates in connecting tech and real cases.” Startups never lack dreamers, but only doers last. At this point, Infervision is a model in the industry and in the leading rank of applying AI tech into real practice. Dated June 2018, over 150 hospitals in national wide have installed Infervision’s star product series InferRead. InferRead could provide averagely 13,000 cases of CT image readings in assisting diagnostic process per day per hospital. Companies with only conceptual ideas and no progress in landing dreams are truly experiencing a capital winter. Technology’s ultimate pursue is servicing human and promote productivity. In 2018, Infervision completed two rounds of funding-- series B closed in February and series C1 completed in this month. Except for Infervision, quite a number of high tech healthcare unicorn companies like 12 Sigma(图玛深维), United Imaging Healthcare(联影医疗),4Paradigm(第四范式),etc. have announced or completed funding series in 2018. Active investments in AI solution may convey a signal to the industry – AI companies should recognize their concept products in reality to survive the winter.  --Author: FU YingWei; write to YingWei at YingWei@EqualOcean.com

News EO
Nov 23, 2018
News EO
Nov 23, 2018

Chinese AI Startup Infervision is Expanding Overseas

Infervision (推想科技), a Beijing-based AI startup using deep learning to improve medical image analysis and help diagnose cancers, recently appointed former GE Healthcare scientist SHEN Yun (沈云) as the president of iCR-inferVISION Global Clinical Collaboration Research Institute. Since China elevated AI as a strategic development plan since 2017, more and more oversea-background scientists returned to China to join the emerging AI gold rush.  CHEN Kuan (陈宽), founder and CEO of Infervision, who himself was a P.H.D. candidate of the University of Chicago, dropped out of his doctoral program after he found the huge opportunities of integrating AI with healthcare industry in 2015. CHEN was right, since been founded in early 2016, his company Infervision has attracted four rounds of funding from various investors, including Sequoia Capital China, Qiming Venture Partners and so on.  Infervision has five products InferRead CT Lung, InferRead DR Chest, InferRead CT Stroke, InferRead CT Bone, and InferScholar Center. All solutions aim to help radiologists to reduce repetitive work and improve the accuracy of diagnosis. Infervision claimed two months ago that the company’s AI imaging technology has been accepted in 200 hospitals worldwide and assists with an estimated 20000 scans for lung cancer screening every day, which made Infervision the largest AI platform in the world (in terms of scan volume) for registered active medical professionals.  Infervision has been actively expanding into international markets in the past year, its Japan and America offices were founded in September 2017, and in March 2018 infervision Europe was launched. “In China, hospitals would like to try new technologies but have little willingness to pay; it’s relatively easier for Infervision to make money from Japan, America, and Europe”, someone familiar with the matter told EqualOcean. 12 SIGMA, a major competitor of Infervision, also takes the same development path. Now Infervision and 12 SIGMA, two Chinese AI medical imaging companies, are racing to rival the same international markets. And just like CHEN, the founder and CEO of 12 SIGMA ZHONG Xin (钟昕), a Carnegie Mellon University graduate who once worked at Qualcomm, discovered the AI tide, back to China and founded 12 SIGMA in 2015. ——Author: YuanPu; Write to YuanPu at YuanPu@EqualOcean.com

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