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Apr 1, 2020 · Deepwise
Analysis EO
Mar 5, 2020
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Analysis EO
Mar 5, 2020

Open Source, Open Mind: Baidu and LinkingMed Help Doctors in Medical Images

LinkingMed has launched its AI-based detection model for pneumonia CT-screening and prediction based on the Baidu’s PaddlePaddle (Parallel Distributed Deep Learning), EqualOcean learned from the medical imaging firm. A Hunan-based hospital affiliated to Xiangnan University became the first medical institution to use the system. This AI-equipped diagnosis system can detect and contour the lesion, picture the diagrams of the density of the two hemisphere lungs, and visualize a series of quantitative benchmarks such as quantity and volume percentage. All these tasks can be completed within less than one minute, with an accuracy rate of  92% - 97%, LinkingMed claims. So far, LinkingMed has not initiated any commercial plans for this AI-based pneumonia detection system. “The motivation to launch this AI medical diagnosis model is only to help fight against the spread of coronavirus,” Mr. Ryan Zhang, the CEO of LinkingMed, said. “We will unconditionally contribute our AI power to containing this plague, as much as we can,” he added. The high-tech medical solution provider focused on solving the compatibility issue with different types of scanning equipment by cooperating with research entities. At the development stage of the algorithm used by the system, the Xiangnan University-affiliated hospital provided professional clinical instructions regarding the data annotation, module design and set strict acceptance criteria to satisfy various medical conditions. This online AI screening system will be deployed at multiple hospitals in Hubei, Chengdu, and other severely-affected areas. Founded in 2016, LinkingMed is an AI technology enterprise in the field of oncological radiation therapy. The Beijing-based medical high-tech company sells techniques and cloud services related to the organic contour, target contour, and radiotherapy to medical institutions. By leveraging the internet and cloud platforms, it also provides remote collaboration and relevant website services for oncological doctors and physicists. During the past four years, LinkingMed has received d four funding rounds, including the recent one worth CNY 40 million in October 2019. Linear Venture is the serial investor for LinkingMed from Series Pre-A finance to the last Series A finance. Medical imaging is a niche business given lightweight and comparably less attention as Chinese medical device makers are promoting their ‘globally competitive’ strategy. Now this area is increasingly highlighted, as the novel coronavirus continues to spread and consumes a lot of medical facilities and doctors across China. The domestic high-tech medical device market rose in 2016, a fierce tussle participated by United Imaging (联影医疗), Huiyihuiying (汇医慧影) and VoxelCloud (体素科技). Most players use essentially indifferent AI technology while base the competency on different sources. These providers still need to consider some fundamental issues to apply AI in daily life. The first is developing the algorithm for the specific problem, for instance, coronavirus event. The other is high-quality data annotation, which takes time and hard work. Additionally, the lack of industry standards, quality protocols, and practice guidelines stand as the major problems ahead of the industry. For patients, time is life. CT imaging plays a critical role in identifying the infected patients, serving as a surrogate to PCR (polymerase chain reaction) diagnostic, according to a previous report. In the Huoshenshan (‘Fire God Mountain) hospital, one of the frontline hospitals, the CT lung screening by InferVision (推想科技) helped with the lab’s capacity as the number of suspected cases rose quickly.  To facilitate the detection process and guarantee the test results, LinkingMed incorporated the AI learning framework into the CT imaging process by utilizing Baidu’s PaddlePaddle. Injected with the AI’s deep-learning power, this open-source online diagnosis model can improve the efficiency and ease the pressure on the clinical doctors.  Before 2020, ‘Artificial Intelligence’ was a buzz word. Now, the outbreak of coronavirus is pushing many key industries to accelerate their AI processes, especially, in the urgent demand for medical facilities. The epidemic has forced Ali Health (阿里健康), Yitu Technology (依图科技), Huawei (华为), Deep Wise (深睿医疗), and other tech companies to introduce their AI-equipped diagnostics, in different aspects, aligning a joint wholistic force to ease the infection.  The PaddlePaddle of Baidu is an open-source deep-learning Chinese platform for industrial applications. Similar to Google’s TensorFlow, PaddlePaddle comprises core learning-framework, model bank, development tool kits, and online services supporting over 1.5 million developers in businesses.  The option to cooperate with PaddlePaddle also indicates LinkingMed’s motivation for its AI diagnostic system. “To curtail the current tension in Korea, Iran, and Japan, we want to provide technical support through Baidu’s platform for international medical institutions and developers,” says Mr. Zhang, “We also will keep an open mind to work with different medical entities, including online healthcare. The goal is to inject technology, whilst fulfilling our social responsibilities. ”

News EO
Sep 16, 2019
report
News EO
Sep 16, 2019

Linking Med Gets Class III, Paving the way for Monetization for the Rest

In August this year the National Medical Products Administration (NMPA) issued a Class III type license to Linking Med (连心医疗), a Beijing-based medical-cloud company that focuses on the processing of oncological medical images. The licensing will facilitate the company’s commercialization of its cloud solution. The first-of-its-kind license is of enormous importance, since it brings the possibility for the other AI-and cloud-driven medical companies to monetize their products.   The company’s cloud solution, which was licensed by the NMPA, has already landed in more than 50 hospitals, serving over 2,000 people per week; since the license was obtained, the cloud-provider has been negotiating the price with hundreds of hospitals, according to VCbeat, a Chinese media organization. NMPA, the regulatory department responsible for the permission and licensing of Class III-type products, took over the duty from the China Food and Drug Administration (CFDA) in 2018, after a major regulatory update by China’s State Council in 2018 that merged the CFDA and several other departments into the NMPA. From 2018 onwards, NMPA has been the official entity that directly reports to the State Council. The medical cloud provider has been generating its revenue from third-party services to the hospital’s radiotherapy departments in China. Since the country has structural problems in cancer treatment that are due to excess demand on very scarce resources, medical cloud and remote consultation have been showing potential as one of the best integrated solutions to the problem, which is Linking Med’s focus. (Check out this in-depth article on China’s structural problems in healthcare). Linear Capital (线性资本) backed health-tech company’s licensing success is good news for the rest of the industry, especially for those who have a medical cloud system that is supported by machine learning and AI. Founded in early 2016, VoxelCloud (体素科技) is one of those companies who provide intelligent cloud systems. Yet another example is 12Sigma (图玛深维), a Jiangsu-based Medical AI developer known for its lung and breast cancer-related MI diagnosis product. Several industry experts have argued that ‘Chinese regulators will not provide a Class III-type of license to any AI-driven medical product in the short-term,’ yet this licensing event shows that the regulators in China are not as ‘conservative’ as some expected. Indeed, it may be just be a beginning for the entire IT and big data-driven healthcare services scene in China. “2019 may be a heaven for monetization in China’s medical AI scene,” once said the CEO of deepwise to EqualOcean. Perhaps he is right in his optimism. 

Analysis EO
Jul 1, 2019
report
Analysis EO
Jul 1, 2019

Interview: 'China's Medical AI Field at Dawn of a Jump' Says Deepwise's CEO

On 28 June 2019, EqualOcean conducted an interview with the co-founder and CEO of Deepwise Healthcare (深睿医疗), Xin Qiao (乔昕), and found the opportunity to know more about the company at first hand. Founded in 2017, Deepwise is a Beijing-based health-tech company that is using AI to diagnose several diseases, including, among others, lung cancer, breast cancer, stroke and bone age interpretation. The company is devoted to optimizing the processes and improving the efficiency of the diagnosis precision.   Here are the key takeaways from the interview:  China's doctor scarcity issue is severe; AI-supported diagnostic products have a non-negligible demand. Deepwise has landed its products in more than 300 hospitals, processing around 40,000 medical images every day, the CEO claimed.  Deepwise "has already started to generate revenue, and its revenues will jump once the company obtains the Registration Certificate for Medical Device III from CFDA," claims the CEO. The CEO has avoided providing any financial data of Deepwise's business or any concrete prediction for the certification date.  Operating from two offices in Beijing and Hangzhou, the company is currently working with around 300 colleagues and 200 freelancer doctors, who labels the raw data for the company. The latest Series C in June will be used to expand the team and research facilities.  The core team members are from Baidu, Siemens and Peking University, which gives a precious technical and intellectual capability to the team. On the other hand, diversified cultures within the team might create a communication problem, and this stands as the biggest challenge for Deepwise to solve.  EqualOcean: How would you evaluate and position China's health-tech industry on a global scale?  Mr Qiao:  China's healthcare demand&supply structure is considerably different from the West. While a general practitioner in the US could spend with each of his/her patients around 30 to 45 minutes, Chinese doctors generally spend around 5 minutes due to the high demand for healthcare and scarce sources in healthcare. These structural problems are a motivation for us to innovate for better solutions.  On the other hand, we're still in the process of catching up with Germany and the US, that are the world's health-tech leaders. Most of the Chinese hospitals are full of imported medical devices from these countries. In fact, we almost have caught them up in some fields such as Medical AI, however, for most of the areas we're still lagged behind, like pharmaceutical and drug developing industry. Yet, the government's support and vision are solid; therefore, I am confident that we will be catching up in the long term.  In Medical AI, our major advantage is the market size and favourable government policies. In China, we have several forms of incentives from public hospitals and government to land our products for the use of hospitals or scientific purposes. On top of that, we have a clear market need for AI supported diagnosis solutions due to the doctor scarcity, especially in the rural areas of China. EqualOcean: Are there high barriers to entry for foreign medical AI companies to conquer the Chinese market?  Mr Qiao: Indeed, barriers are quite high for them. The most significant barrier is medical data accessibility and collection process. Processing, collecting and using medical data is even hard for some SOEs in China, it could be almost impossible for foreign companies. In China, the medical data belongs to the hospital, and if we want to process that data, we need to put our servers into the hospital, as well. For most of the time, medical data cannot leave the walls of the hospital, and we have to adapt to the regulatory environment.  Medical data is technically a complex set of data, and it is strictly forbidden to go across the border unless there is a very particular international scientific collaboration. Therefore we generally see the capital inflow and financial support from overseas investors in China's medical AI field, but not the foreign companies itself. EqualOcean: There are several other companies in the same field. What is the advantage of Deepwise in this competition?  Mr Qiao: Deepwise has a robust LDCT computational database and a diversified team from rooted institutions. Our core team members are the veterans of Pekin University, Badiu and Siemens, and we all have a strong industrial and technical experience, as well as very close relationships with the hospitals and research institutions in China. We also have a 200 people freelancer doctor team who label hundreds of diagnosis entry every day, in a move to boost our machine learning process for Deepwise's decision-making algorithm. It is a transmission from the human brain to the machine.  Thanks to these, we have a vast hospital collaboration network and satisfactory feedbacks for our products.  EqualOcean: How many hospitals have you cooperated so far, and how much revenue has been generated out of these collaborations?  Mr Qiao: We have landed our products in more than 300 hospitals in China, in which more than 20 of them are the most-sought hospitals nationwide. Thanks to this network, our products are analyzing more than 40,000 medical images every day and are getting smarter as it processes more medical data; so we're shifting to higher gears in our already high 95% precision rate. We have already started to generate revenue by several medtech solutions, such as cloud and other services. However, we haven't been able to monetize our AI products that we have been providing for our partners. This is because, in China, there is a strict registration process for medical devices, and Deepwise Healthcare still needs to get the Certificate for Medical Device III from CFDA (China Food and Drug Administration), which is needed to commercialize AI products.  We expect that we will obtain the Certificate in a near future and start to monetize our AI products, which will lead to a massive leap for our revenues and create a monetization paradise for the entire industry.  EqualOcean: What will be the latest Series C be used for?  Mr Qiao: We're going to expand our team and improve the research facilities. Right now, we have 80 computer scientists working with us at our R&D department, and there are 150 colleagues in Beijing, Zhongguancun office. What's more, we have 100 colleagues in Hangzhou office in which around 50 of them are sales-person and BD.  One of the most challenging parts of our operation is to convince the hospital to use our product due to the legal responsibility issues. The hospital always asks us "Who will bear the responsibility in case of a false diagnosis?" and the facts and data always back our answer. After they see that our precision rate is higher than their doctors' average, they are most of the time convinced to accept to use the product. This is a challenging communication process and handled by our 50 persons marketing team.  What are the prospects and challenges of Deepwise?  Mr Qiao: The biggest challenge for me is to manage this very diversified team. Our core members are from Baidu, Peking University and Siemens and all three of them represent different ecoles and cultures. Our colleagues from Peking University are thinking very academic and in a scientific methodology, while Baidu group is very creative and active; the rest is from traditional healthcare companies and fields, and are thinking traditionally. My biggest challenge is to clear the information between them and let them communicate effectively. To solve this problem, I am going to organize more team buildings. (Smiling)  In the long term, we might expand our business overseas; however, our focus is to operate full capacity in China. If we successfully could dominate the market in China, we will start to expand our business overseas and presumably starting from the "One Belt One Road" countries.

News EO
Jun 10, 2019
report
News EO
Jun 10, 2019

Latecomer Deepwise Carries Out its Series C, Securing Fourth Round in Two Years

On June 10, 2019,  Deepwise (深睿医疗) secured its Series C funding round at an undisclosed amount, led by Sunshine Insurance Group (阳光保险集团)), Changfazhan (昌发展), SRHC (丝路华创) and Sunland Fund (蓝资本跟投).  Following this round, Deepwise had undertaken its fourth round of financing since its founding in 2017.  Deepwise, formerly known as AI Lab Project of Peking University, transformed into a profit-maximizing institution in 2017. Boosted by its vast academic and scientific network, Deepwise has landed its products in more than 400 hospitals, in two years.  The company provides AI-driven medical image (MI) diagnostic support solutions, in a move to monetize China's gigantic medical data pool and market. Thus, the company concentrates deep learning powered products and positions itself as one of the most assertive companies amongst several others in China's medical AI field — giving the competitors a run for their money.   Following the latest round, Qiao Xin (乔昕), Co-founder and CEO of Deepwise said that Deepwise would continue to expand its product diversity and further improve products' diagnosis precision thanks to their ever-accelerated deep learning capacity. Medical AI industry has attracted several forms of investors from state-backed funds to the insurance companies. The latest round of Deepwise, for instance, led by an insurance company Sunshine Insurance Group; bringing about an explicit hint for the regulatory atmosphere for the near future of China's medical-AI scene. Prior to Series C, Deepwise had successfully raised around CNY 300 million (USD 43 million) in three rounds of financing, as a one-and-a-half years old startup.  As Deepwise gets momentum at a high-paced, its business prospects and China's medical AI industry gets more mature. There are numerous other Chinese companies on the same scene with Deepwise, such as Huiyihuiying (汇医慧影), 12Sigma (图玛深维), Baheal Intelligent Technology (百洋智能科技), LinkDoc (零氪科技) and others. "China's diagnostic medical imaging market is advanced than of in the US and Japan by a considerable margin, mainly driven by the medical data accessibility and the domestic market," says Anne Ma, the founder and CEO of Shukun Technology, another Chinese AI-diagnosis developer of China. The well-fit market need, regulatory conditions and China's advanced AI scene jointly bring about a developed and diversified medical-AI industry in China.  For a Medtech company that has deep learning and AI at its core, the most critical indicator is its collaborative hospital network and capacity. Mostly, it is significantly challenging for such companies to convince third parties and hospitals to use their product because the stakes are high in the healthcare business.  The C-Suite members and an administrative class of Deepwise are the veterans of either established companies such as GE or affiliated with a highly prestigious research institution, such as Peking University.  This network presents a distinct advantage for the company and allows Deepwise to implement and further develop its learning algorithms; bringing about a grounded possibility for a latecomer to compete with the early-mover heavyweights of the industry. 

Analysis
Jun 10, 2019 · EO Company
News EO
May 9, 2019
report
News EO
May 9, 2019

BGI's Former Director of AI Lab Joins Deepwise

BGI's former director of AI lab, LIU Xiaoqing (刘小青), joins Deepwise (深睿医疗) to open a new chapter in the company's advanced AI R&D facilities. She aims to further develop the decision-making algorithm of Deepwise, particularly in the medical imaging diagnosis product of the company.  BGI (华大基因) is a Shenzhen based genome sequencing company and it is a globally competitive company in its area. A gigantic amount of data is dealt with during a genome sequencing process, and Dr Liu is one of the leaders in this area. She considers precision medicine as a paradigm changer development in medicine. "Unveiling the potential information and the use of deep learning-based visualization technology help doctors to see the huge information that is invisible for the bare eyes. Establishing the confidence of diagnosis executions for the doctors and patients in the medical field will mainly be thanks to the AI technology." Dr. Liu stated. Deepwise is a latecomer Chinese Medical-AI company that is using AI to interpret medical-imaging. Founded in March 2017,  the company successively raised around CNY 300 million (USD 43 million) in 3 rounds of financing in its first year. However, Deepwise's business model has located itself in a highly competitive environment. 12Sigma (图玛深维), Huiyihuiying (汇医慧影), Yitu (依图科技), Infervision (推想科技) are the other major players in AI supported medical image analysis market. Deepwise focuses on Lung and Breast cancer, which are the most problematic types in China. On the other hand, Signify Research expects that Lung and Breast cancer Medical AI analysis applications will occupy around 30% of the entire MI analysis by 2023.  The major products provided by the company are the lung and breast cancer screening and early diagnosis support software. The company claims its lung nodule screening product was able to achieve sensitivity and specificity of 98.6% and 92.9%, respectively. Although Deepwise seems small and non-assertive among the other competitors; the company has attracted the investments and the attention thanks to their administrative team. "The company's executive team's relevant track record and relationships with some of the local governments are impressive," stated EO Healthcare analyst who is familiar with the matter. 

Analysis EO
Nov 26, 2018
Analysis EO
Nov 26, 2018

Deepwise achieved more while the timing was not perfect

November in 2018 must be a critical month for Deepwise (深睿医疗), a Chinese artificial intelligence company developing medical imaging system, and dedicating to using its deep learning technologies in the field of early screening of several kinds of malignant diseases and accurate diagnostic solutions. New products launched According to information from Leiphone.com, Nov 7, 2018, CMA (Chinese Medical Association) held its 25th National Radiology Academic Conference and 26th National Medical Imaging Technology Academic Conference in Beijing. Meanwhile, Deepwise’s new product launch conference was also held successfully. During the conference, Deepwise officially launched its Dr.WiseTM, with 6 products belonging to 4 categories. Dr.WiseTM AI System for Early Cancer Screening, including two products, the latest generation of AI-Assisted Pulmonary Nodule Screening/Diagnosis System and the AI-Assisted Mammography Screening System; Dr.WiseTM AI-assisted Stroke Detection and Analysis System, including Hemorrhagic Stroke Detection as well as Ischemic Stroke Detection; Intelligent Imaging Cloud, Dr.WiseTMCloud; Research platform, Dr.WiseTM Multimodal Research Platform. Endorsement of Deloitte China According to “2018 High-tech and High-growth China Top 50 Report” released by Deloitte China on Nov 20, 2018, Deepwise was listed as one of the “China Rising Star” companies. Candidates of the “China Rising Star” companies should be equipped with leading technology and sustainable business model, and the companies’ industrial segments should have boundless space for growth, in which the companies could enter a leading position in future. The most important indicators of the assessment were the founding team, technological innovation, industry prospects, and corporate valuation. To be listed somehow reflected Deepwise’s certain advantages. Chief Scientist with International Recognition Also in November, Professor YU Yizhou (俞益洲) was elected as a 2018 ACM Distinguished Scientist and 2019 IEEE Fellow. As the co-founder and chief scientist of Deepwise, YU Yizhou and his core algorithm team were said to be the foundation of all the achievements mentioned above, no matter the products or the honors. ACM is the oldest, largest and most authoritative computer professional society in the world. The famous Turing Award is evaluated and promulgated by the organization. ACM Distinguished Scientists must be researchers who made significant achievements and influences in the computer field. Only 49 researchers with outstanding contributions to computer engineering, education, and science have been selected, all over the world. IEEE (Institute of Electrical and Electronics Engineers) is an international association of electronic technology and information science engineers. IEEE Fellow is the highest honor awarded by the organization. It is recognized as an authoritative honor and an important professional achievement in the academic and scientific community. No much time was left for Deepwise Deepwise was actually only a one year and a half startup, founded in Mar 2017 and successfully raised around CNY 300 million (USD 43 million) in 3 rounds of financing in its first year. However, Deepwise’s business prospects are still unclear, even with its launched products and industrial recognition. Until now, AI-assisted medical services, including medical imaging, are still a nice-to-have choice for most of the hospitals, need more tests and demonstrations, as well as the promulgation of relevant laws and regulations, the acceptance of the new technologies wouldn’t be as smooth as other industries. "So far, hospitals shared the data in some way to exchange the use of AI technologies for free, if it is charged, the hospital might reconsider it." A experienced saleperson in the industry told the author. AI algorithms need a large amount of data to improve its accuracy, the latecomer had no any advantages unless it can achieve a breakthrough in medical data acquisition, which was a really big challenge in China. Before Deepwise, AI-assisted medical technology companies had joined the industry since 2012, and 2017 the number of investment events achieved its peak at 45, and there were already dozens of companies in the market, focusing on the similar fields with Deepwise, such as Huiyihuiying.com (汇医慧影), 12Sigma (图玛深维), Baheal Intelligent Technology (百洋智能科技), LinkDoc (零氪科技), etc. Facing the highly competitive environment, Deepwise does need to accelerate its business development. What positive for Deepwise and the industry, would be the huge growth space of the industry, and the great meaning of AI's application in healthcare to serve people better in the future. And besides the traditional hospital, medical imaging diagnosis center could be a better application scenario for the AI-assisted medical imaging technologies. - Author: ZHANG Fan; Write to ZHANG Fan at ZhangFan@EqualOcean.com