Xiaohui Tao

University of Southern Queensland  · School of Sciences

Multimodal medical data fusion has emerged as a transformative approach in smart healthcare, enabling a comprehensive understanding of patient health and personalized treatment plans. In this paper, a journey from data, information, and knowledge to wisdom (DIKW) is explored through multimodal fusion for smart healthcare. A comprehensive review of...

The convergence of systems neuroscience and open science arouses great interest in the current brain big data era, highlighting the thinking capability of intelligent agents in handling multi-source knowledge, information and data across various levels of granularity. To realize such thinking-inspired brain computing during a brain investigation pr...

Machine unlearning (MU) is a field that is gaining increasing attention due to the need to remove or modify predictions made by machine learning (ML) models. While training models have become more efficient and accurate, the importance of unlearning previously learned information has become increasingly significant in fields such as privacy, securi...

Informatics paradigms for brain and mental health research have seen significant advances in recent years. These developments can largely be attributed to the emergence of new technologies such as machine learning, deep learning, and artificial intelligence. Data-driven methods have the potential to support mental health care by providing more prec...

Researchers have been aware that emotion is not one-hot encoded in emotion-relevant classification tasks, and multiple emotions can coexist in a given sentence. Recently, several works have focused on leveraging a distribution label or a grayscale label of emotions in the classification model, which can enhance the one-hot label with additional inf...

Sentiment analysis AKA opinion mining is one of the most widely used NLP applications to identify human intentions from their reviews. In the education sector, opinion mining is used to listen to student opinions and enhance their learning-teaching practices pedagogically. With advancements in sentiment annotation techniques and AI methodologies, s...

Mental healthcare is one of the prominent parts of the healthcare industry with alarming concerns related to patients depression, stress leading to self-harm and threat to fellow patients and medical staff. To provide a therapeutic environment for both patients and staff, aggressive or agitated patients need to be monitored remotely and track their...

Artificial Intelligence (AI) is a fast-growing area of study that stretching its presence to many business and research domains. Machine learning, deep learning, and natural language processing (NLP) are subsets of AI to tackle different areas of data processing and modelling. This review article presents an overview of AI impact on education outli...

The adoption of artificial intelligence (AI) in healthcare is growing rapidly. Remote patient monitoring (RPM) is one of the common healthcare applications that assist doctors to monitor patients with chronic or acute illness at remote locations, elderly people in-home care, and even hospitalized patients. The reliability of manual patient monitori...

The adoption of artificial intelligence (AI) in healthcare is growing rapidly. Remote patient monitoring (RPM) is one of the common healthcare applications that assist doctors to monitor patients with chronic or acute illness at remote locations, elderly people in‐home care, and even hospitalized patients. The reliability of manual patient monitori...

Online learning and teaching increased in 2020, driven by the COVID-19 pandemic. As many researchers attempted to understand the impact stress had on the emotional behaviours and academic performance of students, most studies explored these pre- and during-COVID behaviours in the context of brick and mortar institutions transitioning to online deli...

Information from online platforms is vast, with health related data remaining largely unexplored for the purpose of developing a sentiment-based recommendation model. Though state-of-the-art models such as transformers are being researched in this domain, the model configuration has not been diligently investigated, particularly for deriving qualit...

The field of Natural Language Processing (NLP) has evolved with, and as well as influenced, recent advances in Artificial Intelligence (AI) and computing technologies, opening up new applications and novel interactions with humans. Modern NLP involves machines’ interaction with human languages for the study of patterns and obtaining meaningful insi...

Brain informatics is a novel interdisciplinary area that focuses on scientifically studying the mechanisms of human brain information processing by integrating experimental cognitive neuroscience with advanced Web intelligence-centered information technologies. Web intelligence, which aims to understand the computational, cognitive, physical, and s...

Sentiment analysis AKA opinion mining is one of the most widely used NLP applications to identify human intentions from their reviews. In the education sector, opinion mining is used to listen to student opinions and enhance their learning-teaching practices pedagogically. With advancements in sentiment annotation techniques and AI methodologies, s...

Recent advances in remote patient monitoring (RPM) systems can recognize various human activities to measure vital signs, including subtle motions from superficial vessels. There is a growing interest in applying artificial intelligence (AI) to this area of healthcare by addressing known limitations and challenges such as predicting and classifying...

Recent advances in remote patient monitoring (RPM) systems can recognize various human activities to measure vital signs, including subtle motions from superficial vessels. There is a growing interest in applying artificial intelligence (AI) to this area of healthcare by addressing known limitations and challenges such as predicting and classifying...

Secure deduplication aims to efficiently eliminate redundant data in cloud storage system, where convergent encryption (CE) is widely-used to provide the data confidentiality. As the number of convergent keys (CKs) in CE will increase dramatically with enlarging data, there is a critical issue that how to safely manage the CKs. Previous works usual...

Graph-based multi-view clustering aims to take advantage of multiple view graph information to provide clustering solutions. The consistency constraint of multiple views is the key of multi-view graph clustering. Most existing studies generate fusion graphs and constrain multi-view consistency by clustering loss. We argue that local pair-view consi...

Triaging of medical referrals can be completed using various machine learning techniques, but trained models with historical datasets may not be relevant as the clinical criteria for triaging are regularly updated and changed. This paper proposes the use of machine learning techniques coupled with the clinical prioritisation criteria (CPC) of Queen...

The rapid developments in Artificial Intelligence present an opportunity for the research community to provide and advance Smart Health for the well-being of our society. By considering the availability of multi-source information and heterogeneous data in the era of Big Data, this Special Issue explores the theories, methodologies and possible bre...

Every epidemic affects the real lives of many people around the world and leads to terrible consequences. Recently, many tweets about the COVID-19 pandemic have been shared publicly on social media platforms. The analysis of these tweets is helpful for emergency response organizations to prioritize their tasks and make better decisions. However, mo...

Understanding human intelligence, especially brain intelligence, is the cornerstone of reaching the ultimate AI. In this paper, we briefly review the historical interactions between AI and brain science, and look towards the future vision of AI in the connected world. In particular, we introduce two rapidly developing fields in Web Intelligence (WI...

Database replication is ubiquitous among organizations’ IT infrastructure when data is shared across multiple systems and their service uptime is critical. But complex software will eventually suffer outages due to different types of circumstances and it is important to resolve them promptly and restore the services. This paper proposes an approach...

Public hospitals receive and triage a large volume of medical referrals for otorhinolaryngology annually and it can be a challenge to derive knowledge from them as they are written in unstructured text and may be unavailable in electronic formats. Acquiring knowledge and insights from these referrals are important to public health management and po...

In large MOOC cohorts, the sheer variance and volume of discussion forum posts can make it difficult to for instructors to distinguish nuanced behaviour in students such as positive engagement or stress. Sentiment analysis has been used to build student behavioural models, however, more recent research suggests that separating sentiment and stress...

Modern practices in social commerce are a subset of e-Commerce focusing on security framework protocols such as secure transactional protocols, cryptographic schemes, and sanitization criteria. It is assumed that these practices will ensure stable social media-based e-Commerce applications. The main concern in utilizing these practices focus on sof...

Exploiting hand-crafted lexicon knowledge to enhance emotional or sentimental features at word-level has become a widely adopted method in emotion-relevant classification studies. However, few attempts have been made to explore the emotion construction in the classification task, which provides insights to how a sentence’s emotion is constructed. T...

In recent years, the means of disease diagnosis and treatment have been improved remarkably, along with the continuous development of technology and science. Researchers have spent tremendous time and effort to build models, with an aim to assist medical practitioners in decision-making support. One of the greatest challenges remains is how to iden...

Exploring information processing mechanisms in the human brain is of significant importance to the development of artificial intelligence and translational study. In particular, essential functions of the brain, ranging from perception to thinking, are studied, with the evolution of analytical strategies from a single aspect such as a single cognit...

Due to the rapid growth of Internet, E-commerce and Internet of Things, people use Web based services for most of their needs including buying items, reading books, watching online shows etc. Several companies are using recommender systems to influence people’s choices based on their likings, behaviours etc. Hence, people fear that their privacy is...

With the advances and development of imaging and computer technologies, the application of artificial intelligence (AI) in the processing of magnetic resonance imaging (MRI) data has become a significant research field. Based on 2572 research articles concerning AI-enhanced brain MRI processing, this study provides a latent Dirichlet allocation bas...

Sentiment analysis classification models trained using neural networks require large amounts of data, but collecting these datasets requires significant time and resources. Although artificial data has been used successfully in computer vision, there are few effective and generalizable methods for creating artificial augmented text data. In this pa...

In 2020 the world is facing unprecedented challenges due to COVID‐19. To address these challenges, many digital tools are being explored and developed to contain the spread of the disease. With the lack of availability of vaccines, there is an urgent need to avert resurgence of infections by putting some measures, such as contact tracing, in place....

Remote Patient Monitoring (RPM) has gained great popularity with an aim to measure vital signs and gain patient related information in clinics. RPM can be achieved with noninvasive digital technology without hindering a patient’s daily activities and can enhance the efficiency of healthcare delivery in acute clinical settings. In this study, an RPM...

The application of artificial intelligence (AI) technologies in assisting human electroencephalogram (EEG) analysis has become an active scientific field. This study aims to present a comprehensive review of the research field of AI-enhanced human EEG analysis. Using bibliometrics and topic modeling, research articles concerning AI-enhanced human E...

Data is important for health applications. Clinicians and academics use structured and unstructured data to arrive at both diagnosis and prognosis. Artificial Intelligence (AI) plays a significant role in identifying various clinical diagnostic elements using data. These clinical diagnostic elements are not readily visible to humans. In this tutori...

Recently, Graph Neural Networks (GNN) have been applied to many natural language processing tasks. However, few studies exploit GNN for event detection, especially event detection in social media. In this paper, we proposed a new Event Detection model based on GNN (EDGNN). EDGNN first utilizes a topic model to capture the topical information of the...

This book constitutes revised selected papers from the workshops of the 5th Asia-Pacific Web and Web-Age Information Management International Joint Conference on Web and Big Data, APWeb-WAIM 2021: The Fourth International Workshop on Knowledge Graph Management and Applications, KGMA 2021, The Third International Workshop on Semi-structured Big Data...

Rapid increases in data volume and variety pose a challenge to safe drug prescription for health professionals like doctors and dentists. This is addressed by our study, which presents innovative approaches in mining data from drug corpus and extracting feature vectors to combine this knowledge with individual patient medical profiles. Within our t...

Banking and Financial Services Corporations need to update information systems with logic and data of various applications on everyday basis to remain consistent with change in economy and business activity. This helps to work with latest information included in information system available in current economic and business scenario. This enables in...

Text classification (a.k.a text categorisation) is an effective and efficient technology for information organisation and management. With the explosion of information resources on the Web and corporate intranets continues to increase, it has being become more and more important and has attracted wide attention from many different research fields....

Simile, a special type of metaphor, can help people to express their ideas more clearly. Simile component extraction is to extract tenors and vehicles from sentences. This task has a realistic significance since it is useful for building cognitive knowledge base. With the development of deep neural networks, researchers begin to apply neural models...

Multiple organ failure is the trademark of sepsis. Sepsis occurs when the body's reaction to infection causes injury to its tissues and organs. As a consequence, fluid builds up in the tissues causing organ failure and leading to septic shock eventually. Some symptoms of sepsis include fever, arrhythmias, blood vessel leaks, impaired clotting, and...

Nowadays classification models have been widely adopted in healthcare, aiming at supporting practitioners for disease diagnosis and human error reduction. The challenge is utilising effective methods to mine real-world data in the medical domain, as many different models have been proposed with varying results. A large number of researchers focus o...

The term service component is derived from SCA (service component architecture) for event based distributed system design. Although service component pattern offers composite application development and support application reusability functionality. However, security in event based communication in components interaction model mostly discussed on u...

Computational Social Science (CSS) is the use of Web Intelligence and the tools and technology capable of monitoring, analyzing, diagnosing, and resolving day-to-day problems of society. CSS is the development of intelligent systems and solutions to address the critical problems of the society such as poverty and hunger, slavery and torture, diseas...

Applying Pearson correlation and semantic relations in building a heterogeneous information graph (HIG) to develop a classification model has achieved a notable performance in improving the accuracy of predicting the status of health risks. In this study, the approach that was used, integrated knowledge of the medical domain as well as taking advan...

Evolutionary behavior of Online Social Networks (OSNs) has not been well understood in many different aspects. Although there have been many developments around social applications like recommendation, prediction, detection and identification which take advantage of past observations of structural patterns, they lack the necessary representative po...