Latest AI and machine learning research in staffing & scheduling for healthcare professionals.
Drone-based RGBT object detection plays a crucial role in many around-the-clock applications. However, real-world drone-viewed RGBT data suffers from the prominent position shift problem, i.e., the position of a tiny object differs greatly in different modalities. For instance, a slight deviation of a tiny object in the thermal modality will induce it to drift from the main body of itself in the...
OBJECTIVES: This review summarizes the current and potential uses of artificial intelligence (AI) in the current state of clinical microbiology with a focus on replacement of labor-intensive tasks.
EEG-based neural networks, pivotal in medical diagnosis and brain-computer interfaces, face significant intellectual property (IP) risks due to thei...
Modeling user behavior sequences in recommender systems is essential for understanding user preferences over time, enabling personalized and accurat...
Increasing the volume of training data can enable the auxiliary diagnostic algorithms for Autism Spectrum Disorder (ASD) to learn more accurate and ...
The search for image compression optimization techniques is a topic of constant interest both in and out of academic circles. One method that shows ...
The development in Artificial Intelligence (AI) offers transformative potential for redefining student assessment methodologies. This paper aims to ...
Atherosclerosis is a chronic inflammatory disease of the artery wall. The early stages of atherosclerosis are driven by interactions between lipids ...
Droplet-based communications has been investigated as a more robust alternative to diffusion-based molecular communications (MC), yet most existing ...
Continual Learning in Visual Question Answering (VQACL) requires models to learn new visual-linguistic tasks (plasticity) while retaining knowledge ...
Machine Unlearning allows participants to remove their data from a trained machine learning model in order to preserve their privacy, and security. ...
Contrastive language-image pretraining (CLIP) has significantly advanced image-based vision learning. A pressing topic subsequently arises: how can ...
Materials design is an important component of modern science and technology, yet traditional approaches rely heavily on trial-and-error and can be i...
Code review is an important practice in software development, yet it is time-consuming and requires substantial effort. While open-source datasets h...
Large language models have been widely applied, but can inadvertently encode sensitive or harmful information, raising significant safety concerns. ...
Recent advances in foundation models have brought promising results in computer vision, including medical image segmentation. Fine-tuning foundation...
Large multimodal models (LMMs) demonstrate impressive capabilities in understanding images, videos, and audio beyond text. However, efficiently serv...
OBJECTIVE: This study aims to assess the performance of machine learning (ML) techniques in optimising nurse staffing and evaluating the appropriatene...
Protein structure holds immense potential for pathogenicity prediction, albeit structure-based predictors are limited compared to the sequence-based c...
The coronavirus disease 2019 (COVID-19) pandemic necessitated a shift in healthcare delivery, emphasizing the need for remote patient monitoring (RPM)...