Latest AI and machine learning research in surveys for healthcare professionals.
Edge-cloud collaborative computing (ECCC) has emerged as a pivotal paradigm for addressing the computational demands of modern intelligent applications, integrating cloud resources with edge devices to enable efficient, low-latency processing. Recent advancements in AI, particularly deep learning and large language models (LLMs), have dramatically enhanced the capabilities of these distributed s...
The widespread integration of face recognition technologies into various applications (e.g., access control and personalized advertising) necessitates a critical emphasis on fairness. While previous efforts have focused on demographic fairness, the fairness of individual biological face components remains unexplored. In this paper, we focus on face component fairness, a fairness notion defined b...
In a world where technology is increasingly embedded in our everyday experiences, systems that sense and respond to human emotions are elevating dig...
Large language models (LLMs) have achieved impressive performance across various domains. However, the substantial hardware resources required for t...
Parkinsons Disease (PD) is a progressive neurological disorder that primarily affects motor functions and can lead to mild cognitive impairment (MCI...
Existing saliency detection methods struggle in real-world scenarios due to motion blur and occlusions. In contrast, spike cameras, with their high ...
The incidence of TB in Taiwan declined by 62% from 2005 to 2023 (i.e., from 73/100,000 to 28/100,000). Here we review the past two decades of TB epide...
Preeclampsia remains a leading cause of maternal and perinatal morbidity and mortality worldwide. While traditional prediction models have shown limit...
Efficient prediction of pollutant concentrations in constructed wetlands is critical for optimizing treatment performance, yet existing methodologies ...
Representation bias in health data can lead to unfair decisions and compromise the generalisability of research findings. As a consequence, underrepre...
Despite growing awareness of problems with fairness in artificial intelligence (AI) models in radiology, evaluation of algorithmic biases, or AI biase...
Purpose To assess patient perceptions of artificial intelligence (AI) use in the interpretation of screening mammograms. Materials and Methods In a pr...
Background Four-dimensional (4D) flow MRI provides assessment of thoracic aorta hemodynamic measures that are increasingly recognized as important bio...
Artificial intelligence (AI), a branch of computer science focused on developing algorithms that replicate intelligent behaviour, has recently been us...
BackgroundWith the advancement of Artificial Intelligence (AI), clinical engineering has witnessed transformative opportunities, enabling predictive m...
Virtual reality (VR) is increasingly used to enhance the ecological validity of motor control and learning studies by providing immersive, interacti...
Generative Artificial Intelligence (GenAI) is rapidly reshaping the global financial landscape, offering unprecedented opportunities to enhance cust...
Generative artificial intelligence (AI), particularly large language models (LLMs), is being rapidly deployed in recruitment and for candidate short...
Alzheimer's Disease (AD) is marked by significant inter-individual variability in its progression, complicating accurate prognosis and personalized ...
A person downloading a pre-trained model from the web should be aware of its biases. Existing approaches for bias identification rely on datasets co...