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Publications (34)
Poor air quality has extremely detrimental health consequences, including cancer, stroke, asthma or heart disease. Existing research on air pollution-induced environmental injustice (EI) in Hong Kong (HK) is based on sparse air pollution data due to the limited number of pollution monitoring stations, rendering the study of the relationship between...
Subjective well-being (SWB) refers to people's subjective evaluation of their own quality of life. Previous studies show that environmental pollution, such as air pollution, has generated significant negative impacts on one's SWB. However, such works are often constrained by the lack of appropriate representation of SWB specifically related to air...
This study examines the statistical relationship be- tween people’s international movements and air quality. Utilizing randomized geo-tagged tweets obtained from Twitter Streaming API, we extract international movements that Twitter users have actually made. Coupling these movements with the air quality data across the world, we verify that Twitter...
Alzheimer's Disease (AD) affects over 55 million people globally, yet the key genetic contributors remain poorly understood. Leveraging recent advancements in genomic foundation models, we present the innovative Reverse-Gene-Finder technology, a ground-breaking neuron-to-gene-token backtracking approach in a neural network architecture to elucidate...
Alzheimer’s Disease (AD) significantly aggravates human dignity and quality of life. While newly approved amyloid immunotherapy has been reported, effective AD drugs remain to be identified. Here, we propose a novel AI-driven drug-repurposing method, DeepDrug, to identify a lead combination of approved drugs to treat AD patients. DeepDrug advances...
Although COVID-19 appears to be better controlled since its initial outbreak in 2020, it continues to threaten citizens in different communities due to the unpredictability of new strains. The global viral pandemic has resulted in over 700 million infections and 7 million deaths worldwide, with 22 million cases occurring in the United Kingdom (UK)....
SARS‐CoV‐2 Omicron and its sub‐lineages have become the predominant variants globally since early 2022. As of January 2023, over 664 million confirmed cases and over 6.7 million deaths had been reported globally. Current infection models are limited by the need for large datasets or calibration to specific contexts, making them difficult to apply t...
Alzheimer's Disease (AD) is the 7th leading cause of death worldwide. 95% of AD cases are late-onset Alzheimer's disease (LOAD), which often takes decades to evolve and become symptomatic. Early prognosis of LOAD is critical for timely intervention before irreversible brain damage. This study proposes an Artificial Intelligence (AI)-driven longitud...
Alzheimer's Disease (AD) significantly aggravates human dignity and quality of life. While newly approved amyloid immunotherapy has been reported, effective AD drugs remain to be identified. Here, we propose a novel AI-driven drug-repurposing method, DeepDrug, to identify a lead combination of approved drugs to treat AD patients. DeepDrug advances...
Portable Sensor Nodes (PSNs) can supplement geographically sparse government-run static air quality monitoring stations (AQMSs). A PSN typically consists of several low-cost pollution sensors for different air pollutants, which must be calibrated to improve the accuracy of measurements. These sensors can be co-located with the high accuracy monitor...
Post-traumatic Stress Disorder (PTSD) is a common debilitating mental disorder, that occurs in some individuals following extremely traumatic events. Traditional identification of Genetic Markers (GM) for PTSD is mainly based on a statistical clinical approach by comparing PTSD patients with normal controls. However, these statistical studies prese...
SARS-CoV-2 Omicron has become the predominant variant globally. Current infection models are limited by the need for large datasets or calibration to specific contexts, making them difficult to cater for different settings. To ensure public health decision-makers can easily consider different public health interventions (PHIs) over a wide range of...
The Fukushima Daiichi nuclear disaster has rekindled the world's attention to nuclear safety following the devastating nuclear accidents that occurred in the Three Mile Island and Chernobyl. As China continues to expand in nuclear power development, how it views and responds to nuclear safety carries significant implications on its nuclear safety a...
Cell segmentation plays a crucial role in understanding, diagnosing, and treating diseases. Despite the recent success of deep learning-based cell segmentation methods, it remains challenging to accurately segment densely packed cells in 3D cell membrane images. Existing approaches also require fine-tuning multiple manually selected hyperparameters...
Air pollution presents a serious health challenge in urban metropolises. While accurately monitoring and forecasting air pollution are highly crucial, existing data-driven models have yet fully captured the complex interactions between the temporal characteristics of air pollution and the spatial characteristics of urban dynamics. Our proposed Deep...
This study investigates thoroughly whether acute exposure to outdoor PM 2.5 concentration, P, modifies the rate of change in the daily number of COVID-19 infections (R) across 18 high infection provincial capitals in China, including Wuhan. A best-fit multiple linear regression model was constructed to model the relationship between P and R, from 1...
All people in the world are entitled to enjoy a clean environment and a good quality of life. With big data and artificial intelligence technologies, it is possible to estimate personalized air pollution exposure and synchronize it with activity, health, quality of life and behavioural data, and provide real-time, personalized and interactive alert...
This is a report of the RGC-TBRS funded observational pilot study which examines the effects of personal exposures to three types of air pollutants, namely, PM1.0, PM2.5, and PM10, on personal health condition and perception of young asthmatics (aged 12 to 15) in Hong Kong. This is the first study to investigate the relationship between PM1.0 and F...
Air pollution has long been a serious environmental health challenge, especially in metropolitan cities, where air pollutant concentrations are exacerbated by the street canyon effect and high building density. Whilst accurately monitoring and forecasting air pollution are highly crucial, existing data-driven models fail to fully address the comple...
Background: This paper investigates the statistical relationship between bilingualism and the Onset Age (OA) of AD and MCI across a clinical sample, consisting of 580 Alzheimer's Disease (AD) subjects and 1264 Mild Cognitive Impairment (MCI) subjects, via a statistical analysis conducted on the sample retrieved from the Alzheimer's Disease Neuroima...
For over three decades, air pollution has been a major environmental challenge in many of the fast-growing cities of the world, including Beijing, China. Given that any long-term exposure to high levels of air pollution has devastating health consequences, accurately monitoring and reporting air pollution information to the public is critical for e...
This study examines the statistical relationship between people's movements and difference in air quality between the origin and the destination, using computational social science approach. We put forward an important environmentally driven human movement question: Would people move to places of better air qualities? Utilizing Twitter Streaming AP...
Rapid socio-economic development and urbanization have resulted in serious deterioration in air-quality in many world cities, including Beijing, China. This study attempts to examine the effectiveness of air pollution control regulations implemented in Beijing during 2008–2019 through a data-driven regulatory intervention analysis. Our proposed Bay...
Attempts have been made to estimate PM
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and PM
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values from smartphone images, given that deploying highly accurate air pollution monitors thro...
Predicting air pollution concentration is crucial and beneficial for public health. This study proposes a domain-specific Bayesian deep-learning model for long-term air pollution forecast in China and the United Kingdom. Our proposed model carries three novelties: First, a domain-specific knowledge is integrated to take into account the strong stat...
Background
Motivated by the findings that exposure to daily outdoor PM 2.5 (P) may increase the risk of influenza infection, our study examines if immediate exposure to outdoor P will modify the rate of change in the daily number of COVID-19 infections (R), for (1) 31 Chinese provincial capital cities and (2) Wuhan, China, using regression modellin...
Background: A novel coronavirus was detected in Wuhan, China and reported to WHO on 31 December 2019. WHO declared a global pandemic on 11 March 2020. The first case in the US was reported in January 2020. Since mid-March 2020, the number of confirmed cases has increased exponentially in the States, with 1.1 million confirmed cases, and 57.4 thousa...
In China, one percent of the richest population holds more than one-third of the wealth, while the poorest 25% shares no more than two percent of the total. The country’s rapid economic development has resulted in increasing socio-economic disparities, and a rapidly deteriorating environment. This puts the Chinese citizens, especially the most vuln...
Background: Covid-19 was first reported in Wuhan, China in Dec 2019. Since then, it has been transmitted rapidly in China and the rest of the world. While Covid-19 transmission rate has been declining in China, it is increasing exponentially in Europe and America. Although there are numerous studies examining Covid-19 infection, including an archiv...
Poor air quality has become an increasingly critical challenge for many metropolitan cities, which carries many catastrophicphysical and mental consequences on human health and quality of life. However, accurately monitoring and forecasting air qualityremains a highly challenging endeavour. Limited by geographically sparse data, traditional statist...