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Conference on AI Creating New Paradigms in Healthcare and Medicine Was Successfully Concluded

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A high-tech innovation conference on AI and healthcare and medicine kicked off in our university on 22 October 2021. During the 2021 National Mass Entrepreneurship & Innovation Week in Shenzhen and Shenzhen International Maker Week, the Center for Innovation, Design & Entrepreneurship (CIDE) of the Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen), the School of Medicine (MED) of CUHK-Shenzhen, Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS), the School of Life and Health Sciences (LHS) of CUHK-Shenzhen, Shenzhen Research Institute of Big Data (SRIBD) and the Shenzhen Branch of China Construction Bank jointly held the 2021 Conference on AI Creating New Paradigms on Healthcare and Medicine.

Following the guideline of hosting a high-end, international, professional, market-oriented and intelligent conference, the conference took a people-oriented approach, created a diverse, open and dynamic atmosphere, and attracted scholars, industry elites, and innovative and entrepreneurial talents from around the globe.

In light of the COVID-19 pandemic, the conference was broadcast live globally on Vzan and CIDE official account on Bilibili with Chinese-English simultaneous interpretation which attracted over 395,500 people online, creating a feast of innovation for professionals in AI and healthcare and medicine around the world.

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Moderator

The conference was moderated by Professor Gordon Lam, Co-Director of CIDE of CUHK-Shenzhen. At the beginning of the conference, Professor Lam expressed his warm welcome and heartfelt thanks to the guests and audience who participated in the conference online.

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Top scientists, representatives of international entrepreneurs, experts and scholars, investors and outstanding tech innovation entrepreneurs around the world were invited to participate in the conference, where guests started dialogues on innovation, technology, application, talents and capital introduction by focusing on the latest research on AI.

Opening Speech

Professor Davy Cheng, Founding Dean & Presidential Chair Professor of MED delivered an opening speech. Professor Cheng officially kicked off this innovation-focused conference by sharing a brilliant academic topic with the participants from the three aspects of AI medical technologies, the potential threats of AI healthcare, and the current situation of the marketization of AI medical technology.

Click the picture below to watch the video of Professor Chengs opening speech.

 

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Keynote Speeches

Opening Speech: The Scientific Value of Biocomputing in the Development of Biomedical Industry in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA)

Speaker: Hsien-Da HUANG, Presidential Chair Professor & Associate Dean, LHS

Hsien-Da HUANG, Presidential Chair Professor & Associate Dean of LHS gave a wonderful lecture around the theme. Professor Huang Xianda started from the status quo of biocomputing research in the GBA, focused on both academic research and market commercialization, and expounded the relationship between science, technology and industrial application in depth.

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Keynote Speech I: A Theory of Research & Innovation

Speaker: Xin ZHANG, Associate Dean, AIRS

Xin ZHANG, Associate Dean of AIRS, took the Nokia Bell Labs as an example and delivered a keynote speech on "A Theory of Research and Innovation". Zhang cited the opinions of many senior persons, analyzed the similarities and differences between research and innovation from multiple angles, and conveyed two pieces of advice based on his scientific research and entrepreneurial experience to the audience: 1) Research and innovation are not the same thing and how to ensure the rules to follow when it comes to innovation; 2) AI is a booster that can only be activated when closely integrated with the industry.

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Keynote Speech II: Rapid Detection of Drug-resistant Pathogens Based on AI and MALDI-TOF

Speaker: Tzong-Yi LEE, Associate Professor, LHS

Associate Professor Lee delivered a professional academic report to the audience. Associate Professor Lee said that the drug-resistant pathogen is a health crisis of global concern. He started from how AI could accelerate the detection of drug-resistant pathogens, focusing on the identification process and its advantages, research innovations and challenges, research results and prospects, and in particular the practical application of AI prediction system to clinical healthcare and its effects, as well as how AI could improve antibiotic medication and reduce severe mortality. He gave a systematic and comprehensive introduction of the whole process of the rapid detection of drug-resistant pathogens based on AI and MALDI-TOF.

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Speaker: Michael Ferguson, Senior Associate Dean of the School of Management and Economics (SME) of CUHK-Shenzhen.

After the keynote speeches, Professor Michael Ferguson, Senior Associate Dean of SME delivered a speech and once again expressed his sincere thanks and welcome to the guests and audience for their participation.

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Panel Discussion

In the second half of the conference, the guests had discussions around Whats New for Healthcare Innovation and Investment? With the moderation of Professor Gordon Lam, Co-Director of CIDE of CUHK-Shenzhen, Mr. Michael CHOW, Managing Partner of Radiant Tech Ventures, Mr. Lingxi ZENG, GM of Shenzhen Leaguer Group & Leaguer Biological Technology, Dr. Zhen LI, Assistant Professor of SSE, Dr. Li LIU, Research Scientist of SRIBD, and Dr. Yong LEI, Assistant Professor of MED shared their opinions from different perspectives.

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From the perspective of a capital investor, Mr. Michael CHOW shared with everyone the future development directions of AI + healthcare that have great potentials. For example, AI imaging to assist clinical decision-making, big data for pandemic early warnings, and the Internet of Things connection to home testing devices and medical terminal equipment via 5G, etc. The key is that an R&D project must have the combined resources of data, users and funding in addition to its own technological breakthroughs for it to be truly successful.

Mr. Lingxi ZENG focused on the in-depth integration of AI + drug R&D and talked about the trend of the pharmaceutical industry getting intelligent. In recent years, world pharmaceutical giants such as Johnson & Johnson (J&J) and GlaxoSmithKline (GSK) have entered the era of pharma 2.0" where they use machine intelligence to accelerate the development of innovative drugs, the expansion and diversification of product pipelines, and ushered the pharmaceutical industry onto the journey of intelligence through mergers and acquisitions or strategic cooperation, etc. Since 2020, tech giants such as BAT have recruited AI drug R&D talents, launched a drug discovery platform, and entered the AI ​​new drug R&D field. Mr. Zeng used case studies to analyze the necessity and advantages for Shenzhen and HK to develop the AI-BT industry. Shenzhen Leaguer Biological Technology is cooperating with the Research Institute of Tsinghua University in Shenzhen on the establishment of the AI-BT artificial intelligence biotechnology innovation center, which will include AI ​​pharmaceutical computing platforms for the design, screening, optimization and development of small molecules, protein drugs, genes, cells and biological agents with main functions in target discovery, molecule generation, crystal format optimization, biological efficacy and safety verification, etc. It will provide infrastructure for drug R&D from the computing perspective, and in particular make R&D contributions in terms of digitization and intelligence, to build "new infrastructure for drug R&D" and new industrial ecosystems and promote the development of the AI+BT industry in Shenzhen and Hong Kong.

Dr. Li LIU said that AI is now available everywhere, and AI healthcare is an irresistible trend of the times. She took two ongoing projects (automatic diagnosis of liver fibrosis, and ultrasound image processing of lung lesions in patients with covid) as examples to talk about the wide application of AI in the healthcare system. However, Dr. Liu also pointed out that AI healthcare faces many challenges in its development, such as difficulty in obtaining medical imaging data, unbalanced data sets, high costs for data preprocessing, inconsistent data processing standards, etc. AI healthcare still has lots of room for development.

Dr. Yong LEI focused on the research of gene-editing technology for treatments. He took gene-editing technology and the improvement of sub-health issues as examples to talk about how to use AI healthcare to treat human sub-health issues.

Dr. Zhen LI gave an introduction on an effective kidney tumor segmentation framework based on hybrid models, robust medical image segmentation based on confidence learning, and AI-assisted protein structure prediction and applications, and other research results of medical image processing and protein structure prediction based on deep learning.

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During the panel discussion, the guests expressed their opinions on the current development of AI healthcare. Dr. Li LIU believes that the development of AI healthcare requires strong policy support. Mr. Lingxi ZENG believes in the importance of cross-disciplinary training of talents in both IT and BT, the effective establishment of a tiered structure of talents. Meanwhile, the government should provide special support for the industry, establish a public service platform in this field, make data resources accessible, so as to form the differentiated advantages of the GBA and create a good AI healthcare ecosystem. Mr. Michael CHOW emphasized that entrepreneurs and investors in China should also have an international vision and pay attention to the development of AI healthcare around the world while focusing on the domestic market, as well as strengthen international cooperation while improving their own research and innovation capabilities.

Dialogue with Pioneers in HealthTech

Moderated by Professor Gordon Lam, outstanding entrepreneurs who participated in the panel discussion had visionary analysis and in-depth discussions on the new trends of innovation and entrepreneurship in AI healthcare centering on the theme of Dialogue with Pioneers in HealthTech.

Dr. Yufeng CAI, CEO & Founder of Hunan Zixing Artificial Intelligence, shared his entrepreneurial experience. Dr. Cai said that his company has gradually moved from multi-scenario exploration to research in the specialized field of human chromosome karyotype analysis after entering the field of AI healthcare. In the future, AI will be used in data mining to promote scientific research and application.

Dr. Junxiong ZHENG, Founder & Chairman of Shenzhen ZKOSEMI Technology, focused on AI + laser application in healthcare and gave a structured introduction of the commercial promotion of AI healthcare products by citing 2 examples of AI + laser non-invasive blood glucose testing and AI + laser covid testing. He also put forward the grand vision of a disease-free world.

Mr. Xingang LIANG, Founder & CEO of Aitech Limited, focused more on AI+ medicine projects. Mr. Liang gave an in-depth explanation on how third-party enterprises could use AI to help medical institutions such as hospitals or pharmaceutical factories to improve their efficiency and shared the journey of he and his team developing many software, such as AI in TCM tongue diagnosis, user guided diagnosis & pre-diagnosis, diagnosis assistance, and drug visual recognition, chronic disease personalized monitoring system, etc., which gave the audience a good understanding of the current application mechanism of AI in the healthcare market.

The main entrepreneurial and research field of Dr. Humayun Rashid, CEO of Xavor Corporation, is healthcare for the elderly. He pointed out that AI is not a panacea. The prevention of diseases requires accurate AI prediction, and AI prediction requires a large amount of data learning. Dr. Rashid also advocated that a more accurate Personal Health Data Model should be established based on big data to facilitate the in-depth cooperation between geriatric nursing experts and AI experts, and truly make AI shine in the field of geriatric healthcare.

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Entrepreneurs shared their experiences and lessons in AI healthcare during the panel discussion, providing a valuable reference for those who want to enter or have entered the field. Dr. Yufeng CAI said that there are no fixed models for entrepreneurship. As for where to start or how to start, reasonable decisions must be made based on personal resources and competence. Mr. Xingang LIANG said, Market is very important for the AI healthcare industry. Technologies will become empty talks without a market. Therefore, one must have a full understanding of the current situation of the industry before entering it. Dr. Junxiong ZHENG agreed with Mr. Liang. He also believes that technologies can only be dynamic in a dynamic market. Meanwhile, he also pays lots of attention to team building and development. Dr. Zheng suggested that entrepreneurs should gain some experience in related industries before entering this field to start a business.

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Q&A Session

The audience asked many questions in the Q&A session which the speakers answered with patience. Lets take a look at some wonderful interactions.

Q: Can AI really replace doctors?

Associate Professor Tzong-Yi LEE: AI cannot completely replace the role of doctors now. The diagnosis and treatment of many diseases in the healthcare field require a lot of experience. If AI could also accumulate clinical experience, it may be used as an auxiliary tool for doctors to provide essential information and assistance during diagnosis and treatment, especially during surgery. Many issues related to AI healthcare are indeed worth further exploration and research, but how accurate, fast, and effective can it be? This depends on its development in the future.

Q: Can the drug R&D process be shortened by using AI?

Professor Hsien-Da HUANG: AI can indeed greatly shorten the R&D time and improve R&D efficiency in the process of drug development. Whether it is drug target search, drug development and modification, or drug clinical trial simulation, AI has a big role to play.

Q: What are the professorsopinions on the interpretability/explainability of AI?

Associate Dean Xin ZHANG: AI interpretability is not a necessary condition for the AI model to work reliably. It may only reassure users. The model can be trusted as long as it has been sufficiently verified and has sufficient robustness in sufficiently diverse application scenarios. Instead of focusing on interpretability, it is better to focus on the completeness of the test. For example, if you trust a driver, you dont need to know how every neuron in his brain works. You know that he or she will safely take you to your destination in most cases. There is a very small possibility of accidents due to the driver being out of his or her element one day, but you are willing to accept the risk of such a small probability.

Associate Professor Tzong-Yi LEE: The current problem is the lack of interdisciplinary talents. AI and BI are not interlinked. People who do AI or data science are likely to have little medical knowledge, which makes them unable to interpret some things well. It's not that AI can't interpret it, but the lack of interdisciplinary talents who can interpret it. Even if it cannot be interpreted, the huge contribution of AI in the healthcare field cannot be ignored.

Concluding Remarks

The conference attracted scientists, entrepreneurs, experts and scholars, international organizations and investors to conduct top-level dialogues, promoted technology and innovation collaboration between young people in Shenzhen and Hong Kong in the GBA, and built a platform for innovation and entrepreneurship cooperation and exchange in the GBA, which all help to build a world-class industrial cluster of AI + healthcare.

The success of the conference is inseparable from everyone's support and help. On behalf of CUHK-Shenzhen, CIDE would like to extend our most heartfelt gratitude to the leaders, guests, partners and friends who attended the conference. Lets meet again at the next event.

Click on the image below to watch replay of this event.

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