April 2018 - Page 2 of 9 - Review Game Mobile Hot

AI in Healthcare – Opportunities for Vietnam

“Data is the new oil. It’s valuable, but if unrefined it cannot really be used. It has to be changed into gas, plastic, chemicals, etc to create a valuable entity that drives profitable activity; so must data be broken down, analyzed for it to have value.”
(Clive Humby, UK Mathemetician and architect of Tesco’s Clubcard, 2006)
Healthcare has been long understood as the most promising application area for AI. In the past five years, 300 deals in the field of healthcare AI have been closed, with total investments of over USD 2 billion. This trend is accelerating quickly.
The two most active areas of research and deployment are Medical Imaging & Diagnostics (e.g. automated detection of medical conditions on X-Ray) and Patient Data & Risk Analytics (e.g. identifying patients with high risk of stroke from their past medical record), both of which require vast amount of labeled data.

Dr. Tran Dang Minh Tri (Dimitry Tran) – Harrison-AI (Australia)

In a world where algorithms are open-sourced and processing power is easily accessible over the cloud, the future superpowers in healthcare AI will be the countries that best capture and apply their population’s health data to develop machine learning solutions.
Every single day, each Vietnamese hospital create tens of thousands of new data points – X-Ray images, CT scans, blood tests, disease diagnoses. All these data are the crude oil that currently being wasted. How do we refine this oil to run the healthcare AI machine?
How do we – government, hospitals, tech companies, AI researchers – work together to capture this opportunity and make Vietnam into a healthcare AI superpower in the next 3 years?
Dimitry Tran (Trần Đặng Minh Trí), a health care innovator with bases in Australia and Vietnam, is a co-founder of Harrison-AI with his brother Aengus Tran (Trần Đặng Đình Áng).
Harrison-AI is a Sydney-based healthcare artificial intelligence lab. Taking the implementation path, Harrison-AI seeks to bring the latest developments in AI to solve the biggest challenges in healthcare – making it better and cheaper for all. In 2017, Harrison-AI made a breakthrough in the field of reproductive health. The technology is now patent-pending and undergoing multi-national and multi- centre clinical trial with a global healthcare provider.
Dimitry is the Head of Innovation at Ramsay Health Care – a USD 10 billion enterprise, and one of the largest hospital operators in the world with over 200 facilities in Australia, France, UK, Indonesia and Malaysia. In this role, Dimitry works on growing innovative care models and technologies to expand healthcare services and improve patient outcomes.
He is also a founding investor and on the board of directors of MediRecords.com – the first cloud-based doctor practice management software in Australia.
Dimitry is a Honorary Associate at the Hoc Mai Foundation, a 20-year-old charity operated by University of Sydney Medical School in partnership with Hanoi Medical University. He is also the Co-Founder and Chairman of the Centre for Healthcare Improvement (CHIRvn.org), a social enterprise with the goal of accelerating the pace of change and ‘make healthcare better for patients, professionals and population’ in Vietnam.
Dimitry holds the Chartered Financial Analysts (CFA) designation, Executive MBA degree from the University of New South Wales, and Executive Education Certificate from Harvard Business School. He is studying toward the Master of Applied Science in Patient Safety and Healthcare Quality degree at Johns Hopkins University.
Dimitry graduated first in his class at Bond University, where he completed bachelor degrees in Accounting and Finance and was the recipient of the Dean Scholarship and University Medal.

Fostering the communities of robotics and AI in Vietnam and in International

Siloed development, wasted labor, and high start-up cost are limiting the pace of robotics innovation. With Kambria, our mission is to accelerate this process – enabling faster, cheaper, and easier robotics development and adoption by everyone. In this talk we will discuss the unique game-theoretical design of Kambria based on blockchain and crypto-economics to align the incentives of all key stakeholders in the robotics community. Ultimately, the Kambria platform will foster an ecosystem where collaborators, top developers, and companies, who share our passion for robotics technology will deliver affordable and impactful robots to end users. We will then discuss how Kambria could help build a strong AI and robotics community in Vietnam to capture the upcoming opportunities. We will also give a quick demo of our first robot and an arm prototype manufactured based on 3D-printing technology. Our mission is to equip Vietnam with the engineering talents and the manufacturing capabilities to become a significant AI & Robotics hub in the world.

Dr. Vu Duy Thuc – Ohmilabs (USA)

Graduated from Carnegie Mellon with a BS and Stanford with a PhD both in Computer Science, Ohmnilabs’ CEO and co-founder Thuc Vu is an expert in Artificial Intelligence and Algorithms. His ambition is to bring robots into every home to create a positive impact in people’s life. And Kambria – a decentralized AI and Robotics platform – is his next move to bring this goal one step closer to reality. He previously founded Katango and Tappy which were quickly acquired by Google and Weeby.co, respectively. He also invests in early stage startups and helps grow the ecosystem in Vietnam. Apart from being an entrepreneur, Thuc is also a Research Scientist and Assistant Professor at John Von Neumann Institute of Vietnam National University. As a way to pay it forward, Thuc co-founded VietSeeds in 2011, a nonprofit organization empowering hundreds of underprivileged students with excellent academic record in Vietnam. In 2017, he was named as one of the “40 Under 40” of Silicon Valley by the Silicon Valley Business Journal for his tireless effort to bring about a significantly positive impact in the business world.

NeuroChain: Blockchain gặp Trí tuệ nhân tạo

Tóm tắt: Bài viết mô tả một công nghệ mới dựa trên hệ thống phân tán giống Blockchain và được hỗ
trợ bởi các thuật toán máy học. Công nghệ NeuroChain là sự hợp nhất hoàn hảo giữa Blockchain và
máy học dựa trên ba trụ cột chính sau:
– Đối tượng ra quyết định: Một Chuỗi các Bot
– Bộ các quy tắc: Giao thức Ra quyết định (Proof of Involvement and Integrity & Proof of
Workflow)
– Mạng lưới và phương tiện truyền thông: Pragmatic Communication Channels (giao thức giao
tiếp thích ứng theo hoàn cảnh) và Hệ sinh thái học tập.

Link Tải: https://www.neurochaintech.io/pdf/int/vi-tech-whitepaper.pdf

AI and data in cancer research

Artificial intelligence is playing an increasingly important role in cancer research. Advancement in acquisition technologies has led to largescale data production of various molecular readouts. Coupled with smart learning algorithms, this brings exciting challenges and opportunities for early detection, diagnostic, treatment selection and monitoring of cancers. Is it possible to identify cancers early in a non-invasive manner? Can cross-cancer analysis offer guidance to treatment of patients whose tumors reside in a different organ and yet sharing driver gene mutations with other tumors that have previously been successfully managed?
In this presentation, I will survey current methods and data in cancer genomics and proteomics with a view towards real-life applications. I will also discuss sustainable software tools and computing infrastructures to maintain the momentum of AI in the field of cancer research.

Dr. Pham Viet Thang – VU University Medical Center (Netherland)

Pham Viet Thang received a BSc degree in computer science from RMIT University, Australia in 1998. After a brief period working as teaching assistant at Vietnam National University in 1999, he joined the Intelligent Systems Lab Amsterdam, the Netherland where he earned a doctoral degree on the topic of machine learning and computer vision. During this period, he devised new methods for Bayesian network classification, support vector classification, boosting algorithms, and sparse representation of images. Since 2006, he has been working first as research scientist and now as assistant professor at the Cancer Center Amsterdam, VU University Medical Center, the Netherlands. His current interest is to advance computer algorithms to explore the vast amount of data in cancer research. A highlight of his work is the development of statistical methods for significance analysis of mass spectrometry-based proteomics data.

Application of artificial intelligence techniques in building economic-financial forecast models on high dimensional data sets.

Forecasting in the economic-financial field plays a very important role for the direction and regulation of the government, the development and implementation of business-production strategies of enterprises, investment and consumption of people. So far, the econometric approach based on a combination of mathematics, economic theory and statistical prediction with regression techniques, remains the most popular and important one to make forecasts in the field of economics and finance.
With the increasing economic globalization and the rapid development of science and technology, each event in the field of economics – finance is affected by many other economic-financial and social factors in the country as well as abroad. The current econometric approach to build economic-financial forecasting models is not applicable to input data sets with high dimensions and it is a very big challenge for the implementation of economic-financial forecasts.
The purpose of this report is to present some approachs of application of artificial intelligence techniques in building economic-financial forecasting models on huge input data sets. Artificial intelligence techniques are very useful for dimensionality reduction of input data sets and to improve the quality of forecasting models built under the econometric approach. Some forecasting models in the economic – financial field built arcoding to the mentioned approachs on the real data sets of the economy show that the forecast accuracy by the models is not only increased but also can use these models for evaluation of the impact of economic-financial shocks as well as of many other external factors. Some new researchs by author and some open issues will also be presented and discussed in this report.

Assoc. Prof. Do Van Thanh – Nguyen Tat Thanh University (Vietnam)

Assoc. Prof. PhD. Do Van Thanh was a senior researcher, deputy director of the National Center for Socio-Economic Information and Forecasts, Ministry of Planning and Investment, and a part – time lecturer of the Information Technology Department, University of Technology, Hanoi National University. Now he is a full time lecturer, the Information Technology Department, Nguyen Tat Thanh University. He received PhD’s degree in Information Technology in 1996 from the Vietnamese Academy of Science and Technology. His research interests include Data Analysis and Data Mining, Knowledge representation and automatic reasoning, Economic – Financial Analysis and Forecast. He is the author and co-authors of more than 70 peer – reviewed publications concerning the all fields above. He has strong experience in knowledge discovery in databases and building economic-financial forecast models.