Reading patient data manually takes a huge amount of time. Hence, U.S. Scientists have developed a new, automated, AI-based algorithm that can learn to read patient data from Electronic Health Records (EHR). The scientists, in a side-by-side comparison, showed that their method accurately identified patients with certain diseases as well as the traditional, “gold-standard” method, which requires much more manual labour to develop and perform.
There continues to be an explosion in the amount and types of data electronically stored in a patient’s medical record. Extracting and analysing this complex web of data can be highly ineffective, thus slowing advancements in clinical research.
In this study, we created a new method for mining data from electronic health records with machine learning that is faster and less labour intensive than the industry standard. We hope that this will be a valuable tool that will facilitate further, and less biased, research in clinical informatics.
– Assistant Professor of Genetics and Genomic Sciences
Currently, to mine medical records for new information, scientists rely on a set of established computer programmes or algorithms. A system called the Phenotype Knowledgebase (PheKB) manages the development and storage of these algorithms. While the system is highly effective at correctly identifying a patient diagnosis, the process of developing an algorithm can be very time-consuming and inflexible.
For instance, when researchers want to study disease. They first have to scour through all the medical records to look for relevant information, such as certain lab tests or prescriptions, which are uniquely associated with the disease.
They then programme the algorithm that guides the computer to search for patients who have those disease-specific pieces of data, which constitute a “phenotype”. In turn, the list of patients identified by the computer needs to be manually double-checked by researchers. Each time researchers want to study a new disease, they have to restart the process from scratch. In this study, the researchers tried a different approach in which the computer learns on its own, such as how to spot disease phenotypes and thus save researchers time and effort.
A senior author of the study stated that, previously, the researchers showed that unsupervised machine learning could be a highly efficient and effective strategy for mining EHR. The potential advantage of their approach is that it learns representations of diseases from the data itself. Therefore, the machine does much of the work experts would normally do to define the combination of data elements from health records that best describes a particular disease.
Essentially, a computer was programmed to scour through millions of EHR and learn how to find connections between data and diseases. This programming relied on “embedding” algorithms that had been previously developed by other researchers, such as linguists, to study word networks in various languages. One of the algorithms, called word2vec, was particularly effective. Then, the computer was programmed to use what it learned to identify the diagnoses of nearly 2 million patients whose data was stored in the health system.
Finally, the researchers compared the effectiveness between the new and the old systems. For nine out of ten diseases tested, they found that the new Phe2vec system was as effective as, or performed slightly better than, the gold standard phenotyping process at correctly identifying diagnoses from EHR.
Overall the results are encouraging and suggest that the system is a promising technique for large-scale phenotyping of diseases in EHR data. With further testing and refinement, they hope that it could be used to automate many of the initial steps of clinical informatics research, thus allowing scientists to focus their efforts on downstream analyses like predictive modelling.
Digital transformation made remarkable progress last year, with technology awareness among state agencies, businesses, and citizens significantly improving, according to the Deputy Minister of Information and Telecommunications, Nguyen Huy Dung. He stated that digital transformation has become a trend in the wake of COVID-19. It is a new engine driving the country’s socio-economic development and facilitating virus response and economic recovery. Digital technology has found its way into every governmental, economic, and social activity.
According to a news report, there has been a surge in digitisation across the country. In Da Nang, residents can register for electricity supply and pay power bills via their smartphones. Village chiefs in Lang Son are leading community-based technology groups that teach the villagers how to develop digital shops on e-commerce platforms, helping raise sales of agricultural products 174 times. In Quang Ninh, the chairman of the provincial People’s Committee has deployed a digital system to check the progress of public administrative services delivery.
An industry expert stated that at an early stage, the national digital transformation and the journey towards a digital economy and society still have a long way to go. Every person and business is increasingly aware of how digital technologies are profoundly changing the delivery of public administrative and healthcare services. The national portal for public administrative services has been operational for over a year, with nearly 3,000 services made available.
The remote medical consultation and support network Telehealth, which connects around 1,000 clinics nationwide, has bridged the gap in service quality among regions and reduced overloads at centralised hospitals. Many hospitals now provide digital health records, remote health services, and e-payments.
Do Cong Anh, the Director of the Ministry of Information and Telecommunications’ Information Technology Application, emphasised that it is not only about technology and equipment but also regulatory frameworks, policies, awareness, and personnel. Technology contributes some 20% to an organisation’s successful digital transformation while the remaining 80% depends on its awareness and how its personnel translates digital plans into reality, according to Anh.
By 2030, Vietnam sets to develop an e-government and digital economy which contributes around 30% to the GDP. The country also aims to be among the top 50 countries in e-government development and the third in ASEAN by the end of this decade. Vietnam is expected to be the fastest-growing e-commerce market in Southeast Asia by 2026, with e-commerce gross merchandise value (GMV) reaching US$56 billion by 2026, 4.5 times the estimated value of 2021.
Vietnam is at the forefront of driving change and seizing opportunities to thrive based on digital transformation in a post-pandemic future. A study surveyed about 16,700 digital consumers and more than 20 C-level employees in six Southeast Asian countries, including 3,579 survey participants from Vietnam. The report described Southeast Asia as a leader of digital transformation in the Asia-Pacific region and Vietnam as one of the best performers.
Four research projects led by scholars at City University of Hong Kong (CityU) received grants worth HK$20.26 million in total from the inaugural Green Tech Fund under the Environmental Protection Department, Hong Kong SAR Government.
Established with an allocation of HK$200 million from the Government’s 2020/21 budget, Green Tech Fund aims to boost the research into and development and applications of decarbonisation and green technologies. Addressing issues on decarbonisation, energy efficiency, green transport and air quality, CityU joined with local industries and government departments to expedite low-carbon transformation in Hong Kong.
The project led by Chair Professor of Electrical Engineering received funding worth approximately HK$6.69 million. The objective is to develop a smart power conditioner (SPC) by reusing obsolete electric vehicle (EV) batteries, termed second-life batteries. The overall aim is to improve the power quality and energy efficiency within the electrical distribution network and meet the growing demand for charging EVs.
With an artificial intelligence (AI)-empowered diagnostic framework, the SPC system can estimate the remaining useful life of batteries and the health condition of major power components in the SPC through online monitoring. In addition, the system can help reduce electronic waste by controlling the charging and discharging profiles of the batteries to prolong their life. It can also reduce the power loss of the entire electric distribution network, and solve the frequent failure problems experienced by the power capacitor in the passive harmonic filter and capacitor bank.
A grant of approximately HK$ 5.69 million was awarded to the project led by the Dean and Chair Professor of Atmospheric Environment in the School of Energy and Environment (SEE). The research team will develop two types of portable low-cost sensors for the real-time monitoring of volatile organic compounds (VOCs) in the air. Poisonous VOCs are key precursors of the ozone and suspended particulates that generate photochemical smog.
The two sensing systems that the team plans to develop will be mini metal-organic framework-based photoionisation detector sensors and metal oxide semiconductor sensors; and a portable thermal desorption-gas chromatograph-photoionisation detector system. These systems, which entail lower production costs than existing commercial monitoring devices, will help Hong Kong achieve decarbonisation targets and enhance air quality by controlling the emission of VOCs. In addition, they can be easily installed and are flexible enough for various mobile platforms that monitor VOCs at different horizontal and vertical scales.
The project led by the Director of Hong Kong Institute for Clean Energy and the Professor of Materials Science received funding worth HK$5.03 million. His team will develop highly efficient printable perovskite solar cells (PSCs) to help Hong Kong become a leading city in developing technologies for solar energy.
By developing perovskite as appropriate “ink” for printing films directly on crystalline silicon solar cells, the team aims to produce high-performance perovskite/crystalline silicon tandem solar cells that have 30% higher power conversion efficiency than conventional silicon cells. This technology can enhance the efficiency of photovoltaic systems installed on rooftops. In addition, the team will develop semi-transparent PSCs that can be used as solar windows for building-integrated photovoltaics.
The team consists of top perovskite scientists and experts in printable PSCs. It was noted, currently, more than 85% of energy in the world comes from non-renewable sources. Scientists should therefore bear the responsibility of developing new materials and technologies that will provide highly efficient and sustainable clean energy.
The Associate Professor of SEE was granted approximately HK$2.88 million for his project. Given the prevalent trend for developing green energy through the use of solar energy and water to generate hydrogen, the research team will develop a novel and large-scale photocatalyst panel for solar hydrogen evolution using water from various sources.
The team will put bismuth-based photocatalytic powder developed by Dr Ng on stainless steel plates with a transparent window as an outer frame for receiving sunlight. A thin layer of water (less than 1 cm) will be filled within the photocatalyst panels to generate hydrogen. The clean hydrogen produced by sunlight and water can generate electricity for small indoor devices.
Researchers have developed a new technique, that improves the ability of Artificial Intelligence programs to identify three-dimensional objects, and how those objects relate to each other in space, using two-dimensional images. For example, the work would help the AI used in autonomous vehicles navigate in relation to other vehicles using the 2D images it receives from an onboard camera.
We live in a 3D world, but when you take a picture, it records that world in a 2D image. AI programmes receive visual input from cameras. So if we want AI to interact with the world, we need to ensure that it is able to interpret what 2D images can tell it about 3D space. In this research, we are focused on one part of that challenge: how we can get AI to accurately recognise 3D objects—such as people or cars—in 2D images, and place those objects in space.
– Tianfu Wu, Professor of Electrical and Computer Engineering at North Carolina State University
While the work may be important for autonomous vehicles, it also has applications for manufacturing and robotics. In the context of autonomous vehicles, most existing systems rely on lidar—which uses lasers to measure distance—to navigate 3D space. However, lidar technology is expensive. And because lidar is expensive, autonomous systems don’t include much redundancy. For example, it would be too expensive to put dozens of lidar sensors on a mass-produced driverless car.
If an autonomous vehicle could use visual inputs to navigate through space, you could build in redundancy. Because cameras are significantly less expensive than lidar, it would be economically feasible to include additional cameras—building redundancy into the system and making it both safer and more robust. Specifically, the technique is capable of identifying 3D objects in 2D images and placing them in a “bounding box,” which effectively tells the AI the outermost edges of the relevant object.
The technique builds on a substantial amount of existing work aimed at helping AI programs extract 3D data from 2D images. Many of these efforts train the AI by showing it 2D images and placing 3D bounding boxes around objects in the image. These boxes are cuboids, which have eight points—think of the corners on a shoebox. During training, the AI is given 3D coordinates for each of the box’s eight corners, so that the AI understands the height, width and length of the bounding box, as well as the distance between each of those corners and the camera.
The training technique uses this to teach the AI how to estimate the dimensions of each bounding box and instructs the AI to predict the distance between the camera and the car. After each prediction, the trainers correct the AI, giving it the correct answers. Over time, this allows the AI to get better and better at identifying objects, placing them in a bounding box, and estimating the dimensions of the objects.
What sets their work apart is how they train the AI, which builds on previous training techniques. Like the previous efforts, they place objects in 3D bounding boxes while training the AI. However, in addition to asking the AI to predict the camera-to-object distance and the dimensions of the bounding boxes, they also ask the AI to predict the locations of each of the box’s eight points and its distance from the centre of the bounding box in two dimensions.
As reported by OpenGov Asia, a new report showed that Artificial Intelligence (AI) has reached a critical turning point in its evolution. Substantial advances in language processing, computer vision and pattern recognition mean that AI is touching people’s lives daily—from helping people to choose a movie to aid in medical diagnoses.
Researchers at the Indian Institute of Technology Guwahati (IIT-Guwahati) have developed 3D printed urban furniture using construction material made from local industrial wastes. The technology will cut down concrete use by 75%. According to a report, concrete 3D printing is gaining momentum in the building and construction industries. Recent developments in this field such as 3D printed modular houses, pedestrian footbridges, office buildings, public schools, and low-cost toilet units have the potential to initiate a paradigm change in construction.
A statement by the Institution said that the research group used specially developed printable concrete containing industrial wastes as binders to build 3D printed furniture with a seating height of 0.4 m, a width of 0.4 m, and arch-shaped support that was modelled and sliced using SolidWorks and Simplify3D, respectively. The entire unit was printed layer by layer at an 80 mm/s speed, with each layer having a 10 mm height. After the unit was printed, it was covered by moist gunny bags for seven days to cure before being used.
Traditionally, these structures were mould cast, which require more concrete material, labour, and formwork preparation. A representative from IIT-Guwahati noted that the Institute showcased how material-efficient structures can be produced in their lab-scale 3D printer. The goal is to design high-performance concrete mixes made from industrial wastes for printing such complex structures.
The team is now exploring underwater concrete printing and the possibility of printing functional reinforced concrete using low carbon materials. 3D printing of concrete can be a technological solution for reducing carbon footprint in the building and construction industry. The IIT-Guwahati Director explained that in the Indian context, techno-economic analyses must be carried out that not only accounts for environmental sustainability but also aspects relating to cost, quality, labour, and maintenance associated with 3D printing.
The research team believes that the on-demand, on-site 3D concrete printing will have a global impact on versatile construction applications and multi-billion-dollar markets worldwide. The future jobs will be marshalled into design, automation, servicing, and maintenance of digital systems.
Last August, scientists from the International Advanced Research Centre for Powder Metallurgy and New Materials (ARCI) revealed that they successfully managed to repair aero-engine components using 3D printing technology called Directed Energy Deposition (DED). The research team discovered that the technology significantly reduced repair costs and overhaul time. The powders for the DED 3D printing process were created by scientists on their own.
In December, the Indian Institute of Technology in Ropar (IIT-Ropar) installed an EOS M 290 metal 3D printer in its facility. It uses additive manufacturing technology known as selective laser melting to create complex geometrical featured products from various metals and alloys. The metal 3D printer will be used for research and development. This technology is unique in its ability to address existing issues in the conventional powder bed fusion process such as thermal management and slow build rate. IIT-Ropar will focus on conducting workshops and hands-on training for researchers, students, and staff on the technology process.
A thermovoltaic device that will convert infrared energy from waste heat sources into electricity is being developed by the University of South Australia (UniSA) and a green technology company in collaboration with the Innovative Manufacturing Cooperative Research Centre (IMCRC).
The $314,000 research project, based at UniSA’s Future Industries Institute (FII) in Adelaide, will leverage the green tech company’s existing beta-voltaic technology and adapt it to create an efficient cost-effective device known as ‘GenT’.
Waste heat capture and utilisation technology has been identified as a growth area on the Recycling and Clean Energy National Manufacturing Priority Roadmap and represents a key strategy for improving energy efficiency across Australia.
The Managing Director of the tech company stated that the firm was excited to be working with IMCRC and UniSA’s FII to develop a product set to advance energy efficiency across a broad range of industry sectors. He added that the GenT project epitomises the company’s focus, which is to utilise innovative manufacturing and technology to convert underutilised or waste resources into valuable products.
The IMCRC funding will enable the firm to accelerate the commercialisation of its technology by providing the resources we need to construct prototypes and determine their suitability across a range of applications.
UniSA Professor Drew Evans said that FII researchers were looking forward to supporting the company to develop and deliver an Australian technology that has the potential to become a new, renewable energy source for industry. He noted that for UniSA, the GenT project represents a new opportunity for our materials and manufacturing research to drive economic and social impact for our partners and Australia. The GenT project will utilise UniSA researchers expertise in materials R&D to help the company develop a product of significant benefit to Australia’s and the world’s energy sector.
The IMCRC Deputy CEO stated, “The 12-month project is “a great example of how the industry can effectively utilise Australian manufacturing and scientific research expertise to address industry challenges and create scalable solutions to globally relevant issues.”
The global waste heat recovery system market size was valued at US$54.3 billion in 2019 and is expected to grow at a compound annual growth rate (CAGR) of 8.8% from 2020 to 2027. Growing concerns about Greenhouse Gas (GHG) emissions and strict regulations to decrease carbon footprint is projected to be the key driving factors for the growth of the global waste heat recovery system (WHRS) market.
These systems are highly energy-efficient and can generate onsite electricity, as well as reduce overall operational costs. These factors are also likely to boost their demand over the forecast period. Energy-intensive industries including heavy metal manufacturing, chemical, cement, glass, and petroleum refining are some of the key application areas with substantial waste heat recovery potential.
Such systems enable the reuse of flue gases for pre-drying and co-generation in thermal power plants, which increases the thermal efficiency of the system, thereby fuelling the product demand. The presence of major industry participants, such as General Electric and Terrapin, in this region, will further boost the market growth.
The Asia Pacific is projected to be the fastest-growing region at a CAGR of 10.3% over the forecast period. The Asia Pacific was positioned as the largest FDI recipient in the manufacturing sector. Rapid industrialisation along with increasing awareness about the significance of sustainable energy in emerging markets of India and China is likely to bolster the market growth in this region.
China will promote the process of digitalisation in banking and insurance to heighten high-quality development of the sectors, the country’s banking and insurance regulator has said. Banking and insurance institutions should implement supportive digital development plans to better serve the real economy, according to a guideline recently issued by the China Banking and Insurance Regulatory Commission.
Digital transformation of business management, industrial and personal financial services, and the financial market should be strengthened. Meanwhile, more should be done to improve the data governance system as well as management, quality control, and application of data. The guideline also said that institutions should tighten management against risks, enhance data security and improve privacy protection.
China’s latest plan to grow its digital economy will empower national digital transformation, shore up innovation and enable the government to offer more equitable public services. The State Council, China’s Cabinet, unveiled the first five-year plan on the digital economy on Jan 12, highlighting the sector’s role in reshaping the global economic structure and international competition, and rolling out targets for its development through 2025.
The plan laid out measures for upgrading national infrastructure, bolstering the role of data as a production element and promoting the digital transformation of industries. By 2025, the added value of core digital economy industries is expected to account for 10% of GDP, up from 7.8% in 2020.
The plan also pledged to further open up China’s service sector, explore measures to widen market access for new business models in the digital economy and promote globalized development for emerging services such as data storage and cloud computing.
The plan has set a target of increasing China’s gigabit broadband users from 6.4 million in 2020 to 60 million in 2025 and promoting more commercial and large-scale use of 5G. According to the National Development and Reform Commission, China has developed the world’s largest optical fibre network and has the largest number of internet users, a total of 1.01 billion as of last June.
It also leads the world in the development of 5G, with a total of 1.39 million base stations and 497 million 5G device users as of last November, and it has been the world’s largest online retail market for eight consecutive years, with online sales volume hitting 6.1 trillion yuan ($961 billion) in the first half of last year, up 23.2% year-on-year.
A key focus of the initiative is to shore up innovation capacity in key technologies, as the country seeks to boost the research and development of sensors, quantum information, telecommunications, integrated circuits, key software, big data and Artificial Intelligence (AI).
China will continue to promote the healthy growth of the platform economy, encouraging companies to step up the integration and sharing of data, products and content and expand services such as online healthcare. New growth areas in the sector, such as smart sales, unmanned deliveries and smart manufacturing, will also be promoted.
As reported by OpenGov Asia, stronger tech innovation capabilities are facilitating industrial growth in China, which will help further the high-quality development of the nation’s sprawling manufacturing sector. The remark came after China’s industrial output increased 9.6% on a yearly basis in 2021, 1.5 percentage points higher than GDP growth, according to the National Bureau of Statistics.
More capital is going to the high-tech sector, which will also fuel the in-depth integration of the digital and real economies, and facilitate the high-quality development of manufacturing in China. Last year, investment in high-tech industries increased by 17.1%, 12.2 percentage points faster than total investment. Among the total, investment in high-tech manufacturing and high-tech service industries increased 22.2% and 7.9% year-on-year, respectively.
The Directorate General of Higher Education, Research, and Technology (Ditjen Diktiristek) of the Ministry of Education, Culture, Research, and Technology (Kemendikbudristek) is working with a tech company to develop Indonesian digital talents in the field of Artificial Intelligence (AI). The cooperation is stated in a Memorandum of Agreement (MoA) signed by both parties through a virtual ceremony. This collaboration is an effort made by the Directorate General of Higher Education to accelerate the growth of AI talent in Indonesia.
The scope of the collaboration includes improving the competence of human resources at Indonesian universities, through various activities such as AI skills training for lecturers and students, AI curriculum development in universities, translation workshops and research discussions, as well as development and support for the AI startup ecosystem.
Acting (Plt.) Director-General of Higher Education, Research, and Technology Nizam said, the Directorate General of Higher Education is committed to improving the quality of human resources (HR) of higher education, especially in the field of digital technology. This is in line with President Joko Widodo’s direction to prepare millions of Indonesian digital talents to respond to digital transformation.
It is important for us to ensure that our young generation can face this era of the industrial revolution 4.0, especially with the competencies of AI, machine learning, deep learning, and other fields that this industry needs.
– Nizam, Acting (Plt.) Director-General of Higher Education, Research, and Technology
On the same occasion, Plt. Secretary of the Directorate General of Higher Education, Research and Technology Tjitjik Srie Tjahjandarie said that the process of signing this cooperation agreement was the first step to prepare the next generation who are ready to compete and contribute to the development of technology-based multidisciplinary education in Indonesia. Through this program, it is hoped that the development of technology-based education can be evenly distributed in all universities in Indonesia.
This cooperation agreement can be a motivation to develop the abilities of students and alumni as well as the quality of lecturers and teaching staff in universities. In addition, through this development, a superior university curriculum can be created and is suitable for facing challenges in the changing industry 5.0 and 6.0.
Everyone should understand the implications and impact of AI, regardless of the field of study they study because AI can change almost any sector of the economy. The challenge is, not only do people have to focus on science, but people have to bring awareness about AI more broadly across sectors and industries.
As reported by OpenGov Asia, the Minister of Communications and Informatics Johnny G. Plate encourages everyone to continue to improve their quality of life in line with the projected number and types of new jobs due to technology adoption. It is projected that there will be 85 million old jobs that may be lost and 97 million new jobs that may appear, this is due to the division of labour between humans, machines and algorithms. The new jobs require a high level of digital skills and soft skills.
A report shows that in 2025 there will be 43% of industry players who reduce or reduce the number of workers as a consequence of the application of technology integration. Increasing digital skills and soft skills in line with technological developments for the workforce, especially the younger generation of Indonesia, can be done through upskilling and reskilling.
In addition, the Government has also carried out massive infrastructure development, especially in the first period of President Joko Widodo’s leadership. According to the Minister of Communication and Informatics, entering the current era of digital transformation, the development of digital infrastructure has been and is being accelerated by the Government and its partners and needs to be balanced with improving the quality of human resources.