Artificial Intelligence will have a direct impact on Future Urban Planning

When we think about a future city, we imagine flying cars and robots selling coffee when we head out to work, like in a Sci-Fi movie. But upcoming technology, especially Artificial Intelligence has real potential to deeply and fundamentally impact the shape of our cities. AI, at its core, is powered by algorithms.

From a simplified process perspective, data is pumped through these algorithms, or models, to find patterns in data. With enough data and improved accuracy in this pattern recognition, companies/products can generate actionable insights that help a user.

In simple words, AI can be understood as developing machines and enabling them to perform tasks that traditionally require human intelligence like speech recognition, decision making, language translations, etc.

Today, we are used to AI when it comes to face and voice recognition on our smart devices and secretly get excited at the prospect of having self-driving cars transporting us through long and tedious commutes.

This same excitement around AI’s potential to transform urban spaces led us, here at OpenGov, to Ravi Bedi, Technology Innovation Principal Director at Accenture and an SME for Intelligent Automation and AI. He is also the GTM lead for Accenture’s Data Business group in ASEAN and Automation Engineering Lead for APAC.

Ravi first recognises and highlights two fundamental occurrences that one, lots of data is now digital and two, reduction in the cost of processing data (especially with cloud providers). These changes have positioned Automation and AI to play a key role in today’s world.

Moreover, Ravi believes AI technology can drastically improve the planning and functioning in modern cities. He understands Intelligent Automation solutions as a constellation of various technologies, when combined together, represent the functionality of a digital co-worker, encompassing both rules-based activities as well as judgment-based activity.

He believes it is important to focus on creating Intelligent and connected platforms that look at the constellation of various technologies such as blockchain, AR/VR, Robotic Process Automation (RPA), natural language processing (NLP) and computer vision.

Urban Planning and AI is already a hot topic of discussion in the tech world, especially after the release of the study, Artificial Intelligence and Life in 2030, which outlines the dramatic impact Artificial Intelligence (AI) is having and will continue to have for our cities and the way we live and work in them over the next couple of decades.

Ravi too delved deeper in it to explain how Data Analytics solutions, machine learning, and eventually the 3^rd tier of AI solutions using deep learning, will be able to create a digital crystal ball, allowing us to peer into the future, and predict outcomes, with a high degree of accuracy.

He explained that there are three tiers of applications for AI-backed solutions that can be used in Urban Planning:

The first is, Data Analytics, which takes raw data either in real-time or historical, and provides current insights, for example, intelligent traffic lights. Intelligent traffic lights can use data analytics to coordinate and track time changes in traffic lights, based on the current flow of traffic, making daily commutes smoother.

The second tier of AI applications uses Machine learning. Ravi explained, “ML is a more advanced form of AI. When machine learning is applied to data sets, the algorithms look for patterns in the data, in order to make near term predictions and deeper insights into the data.

A good example within urban planning could be road maintenance. Instead of road crews looking round for potholes to repair, or to wait for citizens to complain about potholes, urban planners can use computer vision techniques to collect and annotate data sets, so that machine learning models can be applied to predict which roads will have more “wear and tear”, resulting in potholes. These maintenance crews can then focus their energy on repairing potholes, instead of looking for them.”

The third tier of AI solutions uses Deep Learning: an advanced version of machine learning. Ravi explained, “Deep Learning AI solutions use highly advanced and complex algorithms. Deep learning is used to crunch very large data sets over a fairly long period of time, to be able to give planners, predictive insights, into the data”.

He provided the following example, of how Urban Planners may use Deep Learning techniques to help design the cities of the future. “Assume a city has won the bid to host the next Olympic games. A multi-year project to build all the sporting facilities is underway. Using deep learning models, urban planners will be able to look into the future, and understand how the nature of traffic will change, how to best manage new traffic flows, how best to design the roads leading up to sporting venues and leading away from sporting venues, how best to design new public transportation etc.”.

Further, on the wider debate between the Tech optimists and pessimists on how much we should let AI take control, Ravi is an optimist who believes AI should be democratized and humanized. Today, most major corporations are incorporating AI as an effective tool to boost their businesses and one such example is Netflix that suggests users shows to watch content based on the pattern of previous views.

Hence, as businesses increasingly adopt the AI-first and Data-first approach in their operations, AI is bound to be a prominent trend across various fields in 2020. Enumerating some of them would include: AI improving healthcare accuracy and cost, empowering cybersecurity, enabling more data synthesis methods, driving efficiency in manufacturing, etc.

Despite these current and prospective adaptations and use cases, AI is still in its infancy stage. Currently, we are at the “Narrow AI” solutions stage that translates to applying algorithms to solve very narrow problems of work. But, even within these narrow applications, when AI is applied, it can work at a scale, that far outstrips what a human can and could do.

Hence, while Automation is inevitable, the focus should be on humanizing it. For instance, AI still needs good data to function well. If the data at hand is biased and not curated carefully, the algorithms will learn wrong patterns. In essence, it is equally important that we (tech users) and the governing authorities understand AI’s potential but also be mindful of its limitations to ensure holistic wellbeing in the long run.

Singapore-Australia Forge Green and Digital Shipping Corridor

Australia and Singapore have begun conversations regarding potential areas of collaboration in green and digital shipping, hence, a Singapore-Australia Green and Digital Shipping Corridor will be established by the end of 2025.

This development is consistent with the Green Shipping Cooperation initiative outlined in the Singapore-Australia Green Economy Agreement, which was signed in October 2022 by Singapore’s Minister for Trade and Industry, Gan Kim Yong, and Australia’s Minister for Trade and Tourism, Don Farrell.

This collaboration is being led by Australia’s Department of Infrastructure, Transport, Regional Development, Communications, and the Arts (DITRDCA) and Singapore’s Maritime and Port Authority (MPA), a Statutory Board under Singapore’s Ministry of Transport (MOT).

These agencies are collaborating closely with port operators, appropriate governments, and marine and energy value chain players on both sides of the Atlantic to galvanise action to decarbonise and digitise the shipping industry. DITRDCA and MPA intend to begin by identifying areas of common interest and partnership to minimise carbon emissions in the maritime industry through coordinated initiatives.

This includes developing low- and zero-carbon fuel supply chains, as well as greening port services and shipping operations to speed the development and adoption of green marine fuel sources. Collaboration would also entail the discovery of digital shipping solutions to promote effective port calls and the flow of products, as well as paperless handling between the ports of Australia and Singapore, all of which would assure system interoperability.

Given Australia and Singapore’s extensive cross-border trade, this collaboration is an important step towards determining how both partners can take a worldwide leadership position in streamlining their shipping routes to test and trial green and digital solutions. This highlights the critical role of international cooperation in decarbonising shipping and the maritime economy.

Collaboration supports environmental sustainability by embracing green shipping practices such as using cleaner fuels, optimising routes, and decreasing emissions, lessening the industry’s impact on climate change and maritime ecosystems.

Digital technology provides for more efficient fleet management, route optimisation, and real-time monitoring, leading to fuel savings, lower operational expenses, and increased profitability for shipping businesses.

Digital solutions improve overall efficiency in areas such as logistics, supply chain management, and cargo handling by streamlining operations, automating procedures, and enabling data-driven decision-making.

Collaboration in digital and green shipping makes it possible to use advanced safety measures like remote monitoring systems, predictive maintenance, and better cybersecurity procedures to protect assets, crew, and cargo.

Acting Prime Minister Lawrence Wong said that Singapore and Australia are very important in making the area a place of stability and growth. To stop international rules from falling apart and regional blocs from forming, it is important to keep and improve multilateralism.

He also said that both countries can keep a rules-based system by taking an active role in making global digital trading rules and norms for international trade.

Australia and Singapore have a lot of strategic trust in each other, so their projects can be used as models for wider regional cooperation. By making deals about the digital and green economies and setting new rules for trade in these areas, they can go beyond bilateral agreements and help the whole region.

The collaboration helps bring about stability and growth, which is good for Asia’s future. Singapore and Australia can help keep the region stable and growing while staying true to their shared values and interests if they work together and take an active role.

Logic-Aware Model Transforming Language Understanding

Researchers have developed a logic-aware model that outperforms counterparts 500 times larger in specific language-understanding tasks without human-generated annotations. This model excels in performance while ensuring privacy and robustness, addressing concerns related to the inefficiency and privacy of large AI models.

Although Large Language Models (LLMs) have demonstrated promising abilities in generating language, art, and code, they come with high computational demands, and utilising application programming interfaces for data upload can pose risks to privacy. Smaller models have historically exhibited lesser capabilities, particularly in tasks involving multitasking and weak supervision, than their larger counterparts.

The researchers introduced the concept of “textual entailment” to aid in comprehending various language tasks by these models. In textual entailment, if one sentence (the premise) is true, then it is likely that the other sentence (the hypothesis) is also true. For instance, if the premise states “all cats have tails,” then the theory “a tabby cat has a tail” would be entailed by the premise.

The team’s previous research revealed that this approach, known as an “entailment model,” exhibited less bias than other language models. To leverage this concept, the researchers developed prompts that enable the models to determine if specific information is entailed by a given sentence or phrase across different tasks. This technique enhanced the model’s adaptability to diverse functions without requiring additional training, a phenomenon referred to as zero-shot adaptation.

In the domain of “natural language understanding,” numerous applications rely on discerning the relationship between two text pieces. For instance, in sentiment classification, the statement “I think the movie is good” can be inferred or entailed from a movie review stating, “I like the story and the acting is great,” indicating a positive sentiment. Similarly, in news classification, the topic of a news article can be inferred from its content. For example, the statement “the news article is about sports” can be entailed if the article’s main content reports on an NBA game. The researchers realised that many existing natural language understanding tasks could be reformulated as entailment tasks involving logical inference in natural language.

“Our research focuses on enhancing the capability of computer programs to comprehend and process natural language, which mimics the way humans speak and write,” explains Hongyin Luo, lead author of a new study from MIT CSAIL.

The study introduces entailment models with 350 million parameters that outperform supervised language models with 137 to 175 billion parameters without human-generated labels. This breakthrough can potentially revolutionise AI and machine learning, providing a scalable, reliable, and cost-effective solution for language modelling. Demonstrating the comparable performance of smaller models in language understanding opens avenues for sustainable and privacy-preserving AI technologies.

The model’s performance was enhanced through self-training, learning without human supervision or annotated data. This approach significantly improved results in sentiment analysis, question-answering, and news classification tasks. It surpassed Google’s LaMDA, FLAN, GPT models, and other supervised algorithms in zero-shot capabilities.

The research addresses the challenge of self-training in language models by developing a novel algorithm called ‘SimPLE’ (Simple Pseudo-Label Editing). By reviewing and modifying the initially generated pseudo-labels, the algorithm improves the overall quality of self-generated labels. CSAIL Senior Research Scientist James Glass emphasises that this study introduces an efficient approach for training large language models (LLMs) by framing language understanding tasks as contextual entailment problems and employing a self-training mechanism with pseudo-labelling. It enables the incorporation of substantial amounts of unlabeled text data during training.

“This study demonstrates the feasibility of developing relatively compact language models that excel in benchmark language understanding tasks when compared to models of similar or even larger sizes,” he concludes.

Unveiling Singapore’s Digital Connectivity Blueprint

Singapore’s Minister for Communications and Information, Josephine Teo, unveiled Singapore’s Digital Connectivity Blueprint (DCB), which establishes the orientation for Singapore’s digital connectivity’s next frontier.

Singapore’s Infocomm Media Development Authority (IMDA) partnered with a cloud computing company to launch a Joint Innovation Centre (JIC), a first-of-its-kind in Southeast Asia and appointed 18 high-potential tech professionals as SG Digital Leaders under the SG Digital Leadership Accelerator.

The Blueprint was created in collaboration with the Advisory Panel on Digital Infrastructure, which is co-chaired by Dr Janil Puthucheary, Singapore’s Senior Minister of State, Ministry of Communications and Information, and other industry partners. It outlines strategic priorities and moves into new frontiers to stay ahead of the curve.

Reports cited that Singapore will continue to invest ahead of demand and plan holistically for the whole digital infrastructure stack, including hard infrastructure, physical-digital infrastructure, and soft infrastructure, to guarantee that the digital infrastructure is future-ready.

The nation is committed to staying ahead of the competition by expanding digital connectivity to provide better lifestyles and new opportunities for people and businesses. Hence, Singapore will increase its focus on the following strategic priorities:

Provide enough capacity for underwater cable landings to double in the next ten years.
Within the next five years, build seamless end-to-end 10 Gbps domestic connectivity.
Ensure digital infrastructure has world-class resilience and security.
Create a roadmap for the expansion of new Green Data Centres and push the sustainability envelope.
Increase the use of the Singapore Digital Utility Stack to broaden the benefits of smooth digital transactions.

Also, Singapore will make movements in more fledgling and frontier areas to capitalise on future opportunities:

Push for a Quantum-safe Singapore within the next ten years.
Lay the groundwork for widespread autonomy.
“Green software” to reduce heightened computing by establishing a nascent ecosystem for sustainable software.
Use Low Earth Orbit satellite services to enable creative solutions in critical industries.

The Blueprint lays a solid foundation for Singapore to achieve better opportunities, stronger trust, and empowered communities.

In addition, Tan Kiat How, Singapore’s Senior Minister of State, Ministry of Communications and Information, met with the 18 Singaporeans designated as SG Digital Leaders from 16 companies. This is part of IMDA’s initiatives to develop Singaporean leaders in the ICT ecosystem for leadership roles in the digital economy.

The SG Digital Leaders are founders of high-growth tech start-ups, executives at large corporations (MNCs), and inventors creating world-changing technology. These executives come from a variety of backgrounds, lead regional teams, and have experience in Artificial Intelligence (AI), Machine Learning (ML), data, software, and engineering.

The JIC will provide exclusive access to the latest tech showcases and demonstrations, innovation methodology for successful adoption and deployment, and workshops for design thinking, among other things, to inspire corporates and public sector organisations to accelerate industry innovation and support the growth of promising start-ups.

Modern digital infrastructure is critical to Singapore’s growth and prosperity. Businesses and consumers may access information and services more easily with improved connections, boosting innovation and economic competitiveness.

Process automation and digitalisation increase efficiency and production while decreasing expenses while smart city solutions improve resource management and overall quality of life. A well-developed digital infrastructure ecosystem attracts investments and encourages digital economy growth.

Data-driven decision-making gives policymakers more authority. Singapore’s emphasis on contemporary digital infrastructure positions it as a digital age global leader prepared for long-term growth and development.

AI for Personalised Myeloid Leukaemia Treatment in Singapore

Researchers from Singapore General Hospital (SGH), A*STAR’s Genome Institute of Singapore (GIS), and Duke-NUS Medical School have used artificial intelligence (AI) to speed up the identification of vital biomarkers that can identify patients with chronic myeloid leukaemia (CML) at diagnosis who will not respond to standard therapy.

These patients may be eligible for a life-saving bone marrow transplant in the early stages of the illness with this favourable prognosis.

A genetic mutation that causes a tyrosine kinase enzyme to turn on permanently causes CML, a specific type of blood cancer. In the bone marrow, a blood stem cell experiences a mutation that transforms it into an aggressive leukaemic cell that eventually takes over the creation of healthy blood.

Tyrosine kinase inhibitors (TKI), which turn off the tyrosine kinase that the genetic mutation switched on as a result, are the standard treatment for CML. But not everyone reacts the same way to these medications. Some individuals respond very well to the point that their life expectancy would be regarded as typical, at the other end of the range.

Besides, some individuals do not respond at all, and their sickness develops into a severe condition known as a blast crisis that is resistant to all sorts of conventional therapy.

Finding out if a patient is resistant to TKI therapy earlier could make the difference between survival or early death because the only cure for blast crisis is a bone marrow transplant, which would be most successful when carried out during the early stages of the disease.

“Our work indicates that it will be possible to detect patients destined to undergo blast crisis when they first see their haematologist,” said the study’s senior author and associate professor, Ong Sin Tiong of Duke-NUS’ Cancer & Stem Cell Biology (CSCB) Programme.

He added this may save lives since bone marrow transplants for these patients are most effective during the early stages of CML.

Researchers made an “atlas” of cells by taking samples of bone marrow from six healthy people and 23 people with CML before they were treated. The map let them see the different types of cells in each sample and how many of each type there were. Researchers did RNA sequencing on a single cell and used machine-learning methods to figure out which genes and molecular processes were on and off in each cell.

The work found eight statistically important things about the bone marrow cells before treatment. These things were linked to either sensitivity to treatment with a tyrosine kinase inhibitor or strong resistance to it.

Patients were more likely to react well to treatment if their bone marrow samples showed a stronger tendency toward premature red blood cells and a certain type of “natural killer cell” that kills tumours. As the number of these cells in the bone marrow changed, so did the way the patient responded to treatment.

The study could lead to drug targets that could help people with chronic myeloid leukaemia avoid or delay treatment resistance and blast crisis.

Associate Professor Charles Chuah from Duke-NUS’s CSCB Programme, who is also a Senior Consultant at the Department of Haematology at SGH and National Cancer Centre Singapore (NCCS), cited that the results of treating chronic myeloid leukaemia have gotten much better over the years and that patients now have many options. Knowing which treatment works best for each patient will improve these results even more, and they are excited about the chance of doing so.

The team hopes to use the results to make a test that can be used regularly in hospitals to predict how well a treatment will work.

Digital Sansad 2.0: Revolutionising Parliamentary Proceedings and Citizen Engagement

For India’s newly inaugurated Parliament building, a revamped version of the Digital Sansad app has been launched to provide a platform to stream parliamentary proceedings. The app is revolutionising communication and collaboration among stakeholders in the sector. It will promote transparency in governance and foster citizen engagement by providing easy access to information and facilitating active participation in the democratic process.

The app aims to cater to the diverse needs of Members of Parliament (MPs), government users, citizens, and secretariat personnel. It offers a range of services tailored to each user group, leveraging state-of-the-art technology to provide an enhanced experience, according to the government.

The revamped Digital Sansad is equipped with a diverse range of advanced features. It serves as a centralised hub for accessing various parliamentary resources. It uses AI to transcribe House proceedings in real-time. The technology enables automatic speech recognition, accurately capturing and transcribing word-by-word spoken in Parliament, ensuring a comprehensive and precise record of the proceedings.

By leveraging AI-enabled transcription techniques, the Digital Sansad app guarantees the availability of precise and dependable records without the need for human intervention in the note-taking process. The approach significantly reduces the risk of errors or omissions, ensuring the accuracy of the transcribed content. Furthermore, it streamlines the documentation process and allows for the easy retrieval of information, benefiting not only MPs and researchers but also the broader public on a large scale.

The Digital Sansad app offers several resources and functionalities to boost parliamentary operations. Users can access information on House business, member participation, debates, Q&As, media galleries, and digital libraries. This comprehensive access enables MPs and citizens to stay informed and engaged in the legislative process. Furthermore, the app acts as a bridge between citizens and their representatives by facilitating open dialogue through the Constituency Connect feature.

By simplifying administrative tasks for MPs, the Digital Sansad app saves valuable time and bridges the gap between their legislative responsibilities and the needs of the public. The direct interaction facilitated by the app ensures transparency, accountability, and responsiveness in the parliamentary processes, thereby fostering a robust democracy. The Digital Sansad 2.0 app is accessible on both Android and iOS platforms.

AI is playing an increasingly significant role in governance in India. The government has recognised the potential of AI to enhance decision-making, streamline administrative processes, and deliver efficient public services. It has also highlighted the importance of protecting data and ensuring the responsible use of AI.

Last month, the Indian Institute of Technology Madras (IIT-Madras) established the Centre for Responsible Artificial Intelligence (CeRAI), a multidisciplinary research centre dedicated to promoting ethical and accountable advancements in AI-powered solutions for practical applications.

As OpenGov Asia reported, CeRAI aims to establish itself as a leading research facility at both the national and international levels, focusing on fundamental and applied research in Responsible AI and its direct influence on implementing AI systems within the Indian ecosystem.

CeRAI’s main focus will be on generating high-quality research outputs, such as publishing research articles in high-impact journals/conferences, white papers, and patents, among others. It will work towards creating technical resources such as curated datasets (universal as well as India-specific), software, and toolkits pertaining to the field of Responsible AI.

HKUST Predicting Alzheimer’s Disease with AI

The Hong Kong University of Science and Technology (HKUST) has led an international research team that has made a significant breakthrough in the field of Alzheimer’s disease (AD). They have successfully created an advanced model that uses artificial intelligence (AI) and genetic data to forecast an individual’s susceptibility to AD even before symptoms manifest.

This pioneering study opens up new possibilities for using deep learning techniques in predicting disease risks and unravelling the underlying molecular mechanisms. It has the potential to revolutionise the diagnosis, interventions, and clinical research related to AD and other prevalent conditions like cardiovascular diseases.

In a collaborative effort, the President of HKUST, and the Chair Professor and Director of HKUST’s Big Data Institute, along with their research team, delved into the potential of artificial intelligence (AI), particularly deep learning models, to predict the risk of Alzheimer’s disease (AD) using genetic information.

This study stands as one of the earliest instances of deep learning models being applied to assess AD polygenic risks in both European-descent and Chinese populations. The results demonstrated that these deep learning models outperformed other models in accurately identifying patients with AD and categorizing individuals into distinct groups based on their disease risks linked to various biological processes. This research showcases the promising role of AI in advancing the understanding and prediction of AD, benefiting both populations of European and Chinese descent.

Currently, Alzheimer’s disease (AD) diagnosis heavily relies on clinical assessments involving cognitive tests and brain imaging. However, by the time symptoms become evident, it is often too late for optimal intervention. Hence, early prediction of AD risk holds great potential for improving diagnosis and intervention strategies.

The integration of the advanced deep learning model with genetic testing allows for the estimation of an individual’s lifetime risk of developing AD with an impressive accuracy rate exceeding 70%. This approach presents a promising avenue for identifying individuals at high risk of AD at an earlier stage, enabling timely interventions and enhancing the development of effective strategies to combat the disease.

Alzheimer’s disease (AD) is a hereditary condition influenced by genomic variations. These genetic variants are present from birth and remain consistent throughout an individual’s life. Analysing an individual’s DNA information can provide valuable insights into their predisposition to AD, facilitating early intervention and timely management of the disease. While FDA-approved genetic testing for the APOE-ε4 genetic variant can provide an estimate of AD risk, it may not be sufficient to identify high-risk individuals due to the contribution of multiple genetic factors to the disease.

Therefore, it is crucial to develop tests that integrate information from multiple AD risk genes to accurately assess an individual’s relative risk of developing AD over their lifetime. This comprehensive approach enables a more precise determination of AD risk and enhances our ability to identify individuals who may require targeted interventions and monitoring.

The President of HKUST stated that the study showcases the effectiveness of deep learning techniques in genetic research and predicting the risk of Alzheimer’s disease. This significant breakthrough is expected to expedite large-scale screening and staging of AD risk within the population.

In addition to risk prediction, the approach enables the categorization of individuals based on their disease risk and offers valuable insights into the underlying mechanisms that contribute to the development and advancement of AD. The transformative potential of these findings will help advance the understanding and management of Alzheimer’s disease.

The Chair Professor and Director of HKUST’s Big Data Institute expressed how this study exemplifies the remarkable benefits of applying AI in the realm of biological sciences, particularly in biomedical and disease-related research. By employing a neural network, they successfully captured the complex relationships present in high-dimensional genomic data, resulting in enhanced accuracy in predicting Alzheimer’s disease risk.

Additionally, using AI-driven data analysis without human supervision, the research team successfully categorized individuals at risk into distinct subgroups, shedding light on the underlying mechanisms of the disease. This study highlights the elegant, efficient, and effective nature of AI in addressing interdisciplinary challenges. The Chair Professor firmly believes that AI will play a crucial role in various healthcare domains in the near future.

The study was a collaborative effort involving researchers from the Shenzhen Institute of Advanced Technology, University College London, and clinicians from local Hong Kong hospitals, including Prince of Wales Hospital and Queen Elizabeth Hospital.

The findings of the study have been recently published in Communications Medicine, highlighting their significance in the scientific community. The research team is currently working on further refining the developed model with the ultimate goal of integrating it into standard screening procedures.

Taiwan Strengthens AI-Based Healthcare Solutions

Partnerships between the public and private sectors to provide AI-based healthcare solutions harness the experience and resources of both sectors, enabling collaboration and knowledge-sharing. This collaboration allows for the development of novel technology and solutions to solve complicated healthcare concerns more effectively.

A Taiwanese venture that creates breakthrough medical software has created an upper respiratory tract evaluation software that is powered by medical artificial intelligence (AI). This product is being utilised as an obstructive sleep apnea treatment evaluation programme that can quickly confirm obstructive sleep apnea sites and identify their aetiology, emphasising its utility as a diagnosis reference software for physicians.

Aside from obstructive sleep apnea, rapid upper respiratory tract assessment can be performed to evaluate orthognathic and laryngeal procedures, as well as pediatric sleep breathing patterns. In 2022, the team cooperated with Taichung Veterans General Hospital, a government-owned hospital in central Taiwan, published their clinical trial results in a reputable journal, and employed the software in conjunction with cardiovascular and geriatric health examinations.

Changes in electrocardiography (ECG) signals related to blood glucose, according to a developer of intuitive tools, employed continuous ECG as the basic algorithm to construct a non-invasive continuous blood glucose monitoring system.

This non-invasive continuous blood glucose monitoring device has undergone clinical trials at Kaohsiung Medical University Chung-Ho Memorial Hospital’s Division of Nephrology, and more clinical trials will be done at multiple global sites in the future.

An AI companion diagnostic and screening tool for osteoporosis, sarcopenia, leukaemia, cervical cancer, human papillomavirus infection, bladder cancer, and breast cancer has been developed by a medical solutions firm dedicated to women’s health. Taiwan, Singapore, and Vietnam have all accepted most of these instruments.

Likewise, the medical solutions provider presents world-class smart laboratory solutions such as Data-analysis AI workstations, front-end automatic nucleic acid extraction systems, test reagent kits, and information storage systems.

The primary concentration of an interactive technology corporation is the development of rehabilitation service systems and articulation training platforms. Its Smart Health Promotion Service System combines software and hardware, and it is an innovative and effective smart rehabilitation system that employs the world’s first smart knee guard for detecting surface electromyography (sEMG) signals in conjunction with a retro and interactive somatosensory game.

According to reports, even though shared investments in global digital health increased significantly during the COVID-19 pandemic, enthusiasm in various disciplines has begun to wane since the end of the pandemic.

A substantial quantity of capital has flowed to AI-related startups as the use of AI in the healthcare industry has increased. Statistic reports indicate that AI is most used to: improve workflow and coordination between medical staff; predict hospitalisation or mortality rates; aid in diagnosis; or develop chatbots that respond to symptom-related questions and provide diagnostic confirmation and consultation for patients.

Cardiovascular medicine has surpassed oncology as the most popular discipline for digital health applications in the Asia-Pacific region over the past five years. Chatbots and “digital pharmacies” are the two areas with the most potential for future expansion. About 86% of pharmacy proprietors believe that improving the patient experience is the key to future differentiation from other pharmacies.

Public-private partnerships encourage shared risks and rewards. By pooling resources and expertise, both sectors can share the risks associated with research, development, and implementation of AI-based healthcare solutions. Additionally, successful outcomes can be mutually beneficial, with opportunities for commercialisation, market growth, and economic development.

June 10, 2023

8th Annual Malaysia OpenGov Leadership Forum 2023, 22 JUNE 2023 - CLICK HERE FOR DETAILS

We are creating some awesome events for you. Kindly bear with us.

Artificial Intelligence will have a direct impact on Future Urban Planning

Singapore-Australia Forge Green and Digital Shipping Corridor

Logic-Aware Model Transforming Language Understanding

Unveiling Singapore’s Digital Connectivity Blueprint

AI for Personalised Myeloid Leukaemia Treatment in Singapore

Digital Sansad 2.0: Revolutionising Parliamentary Proceedings and Citizen Engagement

HKUST Predicting Alzheimer’s Disease with AI

Taiwan Strengthens AI-Based Healthcare Solutions

Recommended Stories

Singapore-Australia Forge Green and Digital Shipping Corridor

Logic-Aware Model Transforming Language Understanding

Unveiling Singapore’s Digital Connectivity Blueprint

AI for Personalised Myeloid Leukaemia Treatment in Singapore

Digital Sansad 2.0: Revolutionising Parliamentary Proceedings and Citizen Engagement

HKUST Predicting Alzheimer’s Disease with AI

India’s Mission MAHIR Advancing Power Sector Tech

New Material Boosts Efficiency of Next-Gen Ceramic Fuel Cells

Logic-Aware Model Transforming Language Understanding

Going Cashless: Vietnamese Consumers Embrace Digital Payments

STOU and APU Collaborate for Future Research and Development

Exclusive! Succeed in The Digital Era with Cloud Communications

Unveiling Singapore’s Digital Connectivity Blueprint

MENU

PARTNER

Qlik

PARTNER

CTC

PARTNER

Planview

SUPPORTING ORGANISATION

SIRIM

PARTNER

HashiCorp

PARTNER

IBM