Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

Advances In Artificial Intelligence-Enhanced Electrocardiography: A Pathway Towards Improved Diagnosis And Patient Care.

In recent years, there has been a surge of research focused on the application of artificial intelligence (AI) to electrocardiography (ECG). AI methods, particularly deep neural networks (DNN), have demonstrated their potential in facilitating ECG interpretation and improving patient care decision-making.

Multiple studies have explored the use of DNN for the detection of cardiac rhythm abnormalities, myocardial infarction and cardiac structural changes, demonstrating equal or superior accuracy and sensitivity compared to average cardiologist interpretations. AI algorithms trained on large labelled datasets are also expanding the dictionary of human-defined rules, enabling the identification of traits with unclear diagnostic criteria.

In this Research Topic, we welcome contributions in the form of original research, review, mini review, hypothesis and theory, perspective, that cover, but are not limited to, the following aspects:

- Database use/selection in AI models, with focus on real-world ECG recordings, data augmentation, etc.- The optimal input format for training DNN models: signal-based ECGs, 2D ECG images, or a combination of both.- Trust and interpretability of AI-assisted diagnoses: techniques that can provide visual insights into AI-assisted diagnoses and uncover features imperceptible to the human eye.- The comparative utility of 12-lead ECGs, 3-lead experimental or computationally derived vectorcardiograms (VCGs), and single-lead ECG from wearables and smartwatches, as well as that of several pre-processing techniques.- The optimal AI architecture for training and inference (i.E. Convolutional Neural Networks vs Generative Pretrained Transformers and Vision Transformers).- The combination of AI with wearable devices to enable timely detection of ECG abnormalities during daily activities.

Ongoing research, addressing the unresolved aspects and considerations outlined above, will pave the way for the widespread adoption of AI-enhanced cardiac electrophysiology. By providing more accurate diagnoses, predicting outcomes, identifying and monitoring individuals at higher risk of cardiovascular events, and assisting therapeutic interventions, AI holds great promise for transforming the field of cardiology.

Dr. Remi Dubois declares the consulting fees for scientific expertise provided to Microport CRM. The other Topic Editors declare no conflict of interest.

In recent years, there has been a surge of research focused on the application of artificial intelligence (AI) to electrocardiography (ECG). AI methods, particularly deep neural networks (DNN), have demonstrated their potential in facilitating ECG interpretation and improving patient care decision-making.

Multiple studies have explored the use of DNN for the detection of cardiac rhythm abnormalities, myocardial infarction and cardiac structural changes, demonstrating equal or superior accuracy and sensitivity compared to average cardiologist interpretations. AI algorithms trained on large labelled datasets are also expanding the dictionary of human-defined rules, enabling the identification of traits with unclear diagnostic criteria.

In this Research Topic, we welcome contributions in the form of original research, review, mini review, hypothesis and theory, perspective, that cover, but are not limited to, the following aspects:

- Database use/selection in AI models, with focus on real-world ECG recordings, data augmentation, etc.- The optimal input format for training DNN models: signal-based ECGs, 2D ECG images, or a combination of both.- Trust and interpretability of AI-assisted diagnoses: techniques that can provide visual insights into AI-assisted diagnoses and uncover features imperceptible to the human eye.- The comparative utility of 12-lead ECGs, 3-lead experimental or computationally derived vectorcardiograms (VCGs), and single-lead ECG from wearables and smartwatches, as well as that of several pre-processing techniques.- The optimal AI architecture for training and inference (i.E. Convolutional Neural Networks vs Generative Pretrained Transformers and Vision Transformers).- The combination of AI with wearable devices to enable timely detection of ECG abnormalities during daily activities.

Ongoing research, addressing the unresolved aspects and considerations outlined above, will pave the way for the widespread adoption of AI-enhanced cardiac electrophysiology. By providing more accurate diagnoses, predicting outcomes, identifying and monitoring individuals at higher risk of cardiovascular events, and assisting therapeutic interventions, AI holds great promise for transforming the field of cardiology.

Dr. Remi Dubois declares the consulting fees for scientific expertise provided to Microport CRM. The other Topic Editors declare no conflict of interest.

Cyber Security Prevention, Defenses Driven By AI, And Mathematical Modelling And Simulation Tools

The current dynamic innovation, research, and development in the fields of Artificial Intelligence (AI), Ultra-Smart Computation, Applied Mathematics, Modeling and Simulation, and Fast Internet, promote the creation of Automated Ultra Smart Cyberspace, which opens a new horizon of opportunities for government, business, academia, and industry worldwide. The ubiquitous and pervasive nature of fast Internet access and computer systems interconnectivity 24/7 opens a Pandora's Box for future more sophisticated and damaging cyber threats capable of destroying most critical sectors in national business, industry, and government. To protect Business, Industry, and Government integrity, the application of Artificial Intelligence has become an essential tool in providing effective and real-time cybersecurity solutions capable of detecting and preventing any cyber-attack 24/7.

The main goal of this article collection is to attract subject-related papers that tackle the current state-of-the-art and future directions in research, innovation, and development of the most effective Cyber Security solutions, capable of detecting and preventing the most sophisticated cyber-attacks 24/7. The use of factor with multi-factor analytics (FA) applied in predictive modeling methods may bring to light effective real-time weights reallocation of collected data, while establishing the relevant probability models. The application of AI contributes to fast and effective mitigation and recognition of cyber threats. The research topic promotes multidisciplinary research while bringing together computer scientists and engineers side by side with applied mathematics, information systems, and related engineering and social sciences.

The scope of this Research Topic focuses on Cyber Security, Malware Detection and Prevention Mechanisms, Software and Hardware Security, the IoT and Critical Cyber Infrastructures Security, as well as the Human Factor and Social dimension of Cyber Security.

The incorporation of AI and Machine Learning mechanisms in cybersecurity contributes well to much faster detection and response enabling real-time analysis of large volumes of data. The current application of AI and Machine Learning provides effective protection of an organization's infrastructure. The AI-driven Cybersecurity tools create defensive mechanisms for the organization's macro and micro levels.

The contributions should focus on cyber-threats triggered by Ransomware, Zero-day Exploits, Business Email Compromise (BEC), Cyberwar, Cybercriminals, Applied Mathematical Tools, Modeling Simulation, and state-sponsored threat actors. The Research Topic invites scholastic contributions from Faculty and graduate researchers, as well as industrial and business practitioners working in the field of Cyber Security, AI, Computing, and Applied Mathematics.

The current dynamic innovation, research, and development in the fields of Artificial Intelligence (AI), Ultra-Smart Computation, Applied Mathematics, Modeling and Simulation, and Fast Internet, promote the creation of Automated Ultra Smart Cyberspace, which opens a new horizon of opportunities for government, business, academia, and industry worldwide. The ubiquitous and pervasive nature of fast Internet access and computer systems interconnectivity 24/7 opens a Pandora's Box for future more sophisticated and damaging cyber threats capable of destroying most critical sectors in national business, industry, and government. To protect Business, Industry, and Government integrity, the application of Artificial Intelligence has become an essential tool in providing effective and real-time cybersecurity solutions capable of detecting and preventing any cyber-attack 24/7.

The main goal of this article collection is to attract subject-related papers that tackle the current state-of-the-art and future directions in research, innovation, and development of the most effective Cyber Security solutions, capable of detecting and preventing the most sophisticated cyber-attacks 24/7. The use of factor with multi-factor analytics (FA) applied in predictive modeling methods may bring to light effective real-time weights reallocation of collected data, while establishing the relevant probability models. The application of AI contributes to fast and effective mitigation and recognition of cyber threats. The research topic promotes multidisciplinary research while bringing together computer scientists and engineers side by side with applied mathematics, information systems, and related engineering and social sciences.

The scope of this Research Topic focuses on Cyber Security, Malware Detection and Prevention Mechanisms, Software and Hardware Security, the IoT and Critical Cyber Infrastructures Security, as well as the Human Factor and Social dimension of Cyber Security.

The incorporation of AI and Machine Learning mechanisms in cybersecurity contributes well to much faster detection and response enabling real-time analysis of large volumes of data. The current application of AI and Machine Learning provides effective protection of an organization's infrastructure. The AI-driven Cybersecurity tools create defensive mechanisms for the organization's macro and micro levels.

The contributions should focus on cyber-threats triggered by Ransomware, Zero-day Exploits, Business Email Compromise (BEC), Cyberwar, Cybercriminals, Applied Mathematical Tools, Modeling Simulation, and state-sponsored threat actors. The Research Topic invites scholastic contributions from Faculty and graduate researchers, as well as industrial and business practitioners working in the field of Cyber Security, AI, Computing, and Applied Mathematics.

Pushing New Frontiers In Industrial Automation

At its regional headquarters in Singapore, Emerson launched the Solutions Centre in 2017. This hub for industrial technologies provides digital transformation, industrial software and sustainability-focused solutions tailored to customer needs. Set in a plant-like environment, the centre hosts in-person and virtual sessions where teams can explore Emerson's technologies, identify operational challenges and develop solutions through hands-on workshops.

The city-state is also home to Emerson's Global Additive Manufacturing Centre, which advances the use of precision metal 3D printing in industrial applications. This is supported by facilities producing smart instrumentation, wireless sensors, digital valve controllers and transmitters. 

In addition, Emerson established a Life Science Technology Transfer and Software Research Center at its facility to support the sector's shift from manual recipe transfer processes to a digital production platform.

Its Southeast Asia Service Centre in Singapore – expanded and revamped in 2021 – has helped reduce service and line downtime by up to 80 per cent for customers using large-capacity flow metres that require regular calibration. 

Strategic partnerships further support innovation and capability development. In 2019, Emerson helped launch the Energy and Chemicals Training Centre at Singapore Polytechnic to equip students and professionals with hands-on training and tools for applied innovation in the energy, chemicals and pharmaceutical sectors.

In 2016, it signed a research collaboration agreement with Nanyang Technological University (NTU), leading to the joint creation of a centre focused on applying 3D printing to the manufacture of industrial control valves. The partnership gives NTU students exposure to commercial environments while enabling Emerson to tap into broader research networks to accelerate product development and explore emerging technologies. 

Beyond its core business of industrial automation, Emerson partners with organisations across Singapore as part of its corporate social responsibility efforts. This includes supporting underprivileged communities as well as mentoring children in science.

In September, Emerson reinforced its leadership in industrial automation at the Boundless Automation Summit in Singapore. The event convened industry leaders, experts and customers to discuss a shared vision of intelligent industrial automation and sustainable operations, exploring the latest developments shaping the sector. 

As Emerson continues to advance its Boundless Automation vision through research and collaboration, Mr William Tan, vice president and general manager of Emerson Singapore, reaffirmed its commitment to Singapore and the region. 

"Emerson Singapore marks a monumental 60 years alongside the nation this year," he said. "We recognise the significance of the Asia-Pacific region and our customers' need for a reliable partner to help them innovate and tackle ongoing challenges." 

He added: "We will continue to support them with a robust automation portfolio that helps reduce emissions and improve sustainability. Our Greening By initiatives support the transition to cleaner energy, greater energy efficiency and less waste – drawing on industry experience and strategic partnerships."  Learn how Emerson can help advance automation, sustainability and digital transformation in your enterprise.

---