Computer methods and programs in biomedicine
Jan 6, 2025
The rise in minimally invasive procedures has created a demand for efficient and reliable planning software to predict intra- and post-operative outcomes. Surrogate modelling has shown promise, but challenges remain, particularly in cardiovascular ap...
With the continuous development of intelligent transportation systems, traffic safety has become a major societal concern, and vehicle trajectory anomaly detection technology has emerged as a crucial method to ensure safety. However, current technolo...
OBJECTIVES: Incidentally detected pulmonary nodules present a challenge in clinical routine with demand for reliable support systems for risk classification. We aimed to evaluate the performance of the lung-cancer-prediction-convolutional-neural-netw...
Data uncertainties, such as sensor noise, occlusions or limitations in the acquisition method can introduce irreducible ambiguities in images, which result in varying, yet plausible, semantic hypotheses. In Machine Learning, this ambiguity is commonl...
Accurate forecasting of claim frequency in automobile insurance is essential for insurers to assess risks effectively and establish appropriate pricing policies. Traditional methods typically rely on a Poisson distribution for modeling claim counts; ...
BACKGROUND AND OBJECTIVE: Accurate extraction of retinal vascular components is vital in diagnosing and treating retinal diseases. Achieving precise segmentation of retinal blood vessels is challenging due to their complex structure and overlapping v...
OBJECTIVE: This preliminary study tested whether non-invasive, remote Elastic Scattering Spectroscopy (ESS) measurements obtained in the oral cavity can be used as a proxy to accurately differentiate between patients with laryngeal cancer versus lary...
PURPOSE: To evaluate various supervised machine learning (ML) statistical models to predict anatomical outcomes after macular hole (MH) surgery using preoperative optical coherence tomography (OCT) features.
The proper use of model evaluation metrics is important for model evaluation and model selection in binary classification tasks. This study investigates how consistent different metrics are at evaluating models across data of different prevalence whi...
Neural networks : the official journal of the International Neural Network Society
Dec 18, 2024
Network intrusion detection (NID) is an effective manner to guarantee the security of cyberspace. However, the scale of normal network traffic is much larger than intrusion traffic (i.e., appearing data imbalance problem), which leads to the training...
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