Telemedicine is an emerging development in the healthcare domain, where the Internet of Things (IoT) fiber optics technology assists telemedicine applications to improve overall digital healthcare performances for society. Telemedicine applications a...
OBJECTIVE: The objective of this study is to integrate PICO knowledge into the clinical research text summarization process, aiming to enhance the model's comprehension of biomedical texts while capturing crucial content from the perspective of summa...
With the escalation in the size and complexity of modern Denial of Service attacks, there is a need for research in the context of Machine Learning (ML) used in attack execution and defense against such attacks. This paper investigates the potential ...
Anticipating human decisions while performing complex tasks remains a formidable challenge. This study proposes a multimodal machine-learning approach that leverages image features and electroencephalography (EEG) data to predict human response corre...
Microbiological Rapid On-Site Evaluation (M-ROSE) is based on smear staining and microscopic observation, providing critical references for the diagnosis and treatment of pulmonary infectious disease. Automatic identification of pathogens is the key ...
The development of machine learning (ML) tools in many different medical settings is largely increasing. However, the use of the resulting algorithms in daily medical practice is still an unsolved challenge. We propose an epistemological approach (i....
Medical & biological engineering & computing
Jun 7, 2024
Even though artificial intelligence and machine learning have demonstrated remarkable performances in medical image computing, their accountability and transparency level must be improved to transfer this success into clinical practice. The reliabili...
Medical & biological engineering & computing
Jun 7, 2024
This paper presents the implementation of two automated text classification systems for prostate cancer findings based on the PI-RADS criteria. Specifically, a traditional machine learning model using XGBoost and a language model-based approach using...
Neural networks : the official journal of the International Neural Network Society
Jun 7, 2024
The recent surge in large-scale foundation models has spurred the development of efficient methods for adapting these models to various downstream tasks. Low-rank adaptation methods, such as LoRA, have gained significant attention due to their outsta...
Neural networks : the official journal of the International Neural Network Society
Jun 7, 2024
This paper proposes a novel approach to semantic representation learning from multi-view datasets, distinct from most existing methodologies which typically handle single-view data individually, maintaining a shared semantic link across the multi-vie...
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