Medical & biological engineering & computing
Oct 25, 2024
Deep neural networks (DNNs) have demonstrated exceptional performance in medical image analysis. However, recent studies have uncovered significant vulnerabilities in DNN models, particularly their susceptibility to adversarial attacks that manipulat...
Medical & biological engineering & computing
Oct 25, 2024
Cerebrovascular image segmentation is one of the crucial tasks in the field of biomedical image processing. Due to the variable morphology of cerebral blood vessels, the traditional convolutional kernel is weak in perceiving the structure of elongate...
Neural networks : the official journal of the International Neural Network Society
Oct 25, 2024
Large-scale Language Models (LLMs) utilizing the Chain-of-Thought prompting demonstrate exceptional performance in a variety of tasks. However, the persistence of factual hallucinations remains a significant challenge in practical applications. Preva...
The high binding affinity of antibodies toward their cognate targets is key to eliciting effective immune responses, as well as to the use of antibodies as research and therapeutic tools. Here, we propose ANTIPASTI, a convolutional neural network mod...
BACKGROUND: Sensor-based remote health monitoring is increasingly used to detect adverse health in people living with dementia (PLwD) at home, aiming to prevent hospitalizations and reduce caregiver burden. However, home sensor data is often noisy, o...
IEEE transactions on bio-medical engineering
Oct 25, 2024
OBJECTIVE: To remove signal contamination in electroencephalogram (EEG) traces coming from ocular, motion, and muscular artifacts which degrade signal quality. To do this in real-time, with low computational overhead, on a mobile platform in a channe...
Surrogate optimisation holds a big promise for building energy optimisation studies due to its goal to replace the use of lengthy building energy simulations within an optimisation step with expendable local surrogate models that can quickly predict ...
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Oct 25, 2024
Accurate and automatic segmentation of medical images plays an essential role in clinical diagnosis and analysis. It has been established that integrating contextual relationships substantially enhances the representational ability of neural networks...
International journal of radiation oncology, biology, physics
Oct 24, 2024
PURPOSE: We propose a tumor tracking framework for 2D cine magnetic resonance imaging (MRI) based on a pair of deep learning (DL) models relying on patient-specific (PS) training.
An adnexal mass, also known as a pelvic mass, is a growth that develops in or near the uterus, ovaries, fallopian tubes, and supporting tissues. For women suspected of having ovarian cancer, timely and accurate detection of a malignant pelvic mass is...
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