Medical & biological engineering & computing
Jan 25, 2025
Photoacoustic tomography (PAT) has emerged as a promising imaging modality for breast cancer detection, offering unique advantages in visualizing tissue composition without ionizing radiation. However, limited-view scenarios in clinical settings pres...
Neural networks : the official journal of the International Neural Network Society
Jan 25, 2025
Low-Rank Representation (LRR) methods integrate low-rank constraints and projection operators to model the mapping from the sample space to low-dimensional manifolds. Nonetheless, existing approaches typically apply Euclidean algorithms directly to m...
International journal of legal medicine
Jan 25, 2025
Sex estimation is an important part of skeletal analysis and forensic identification. Traditionally pelvic traits are utilized for accurate sex estimation. However, the long bones, especially humerus, have been proved to be as effective for determine...
AIM: Spine fractures are a frequent and relevant diagnosis, but systematic documentation is time-consuming and sometimes overlooked. A deep learning pipeline for opportunistic fracture detection in computed tomography (CT) spine images of varying fie...
Lung Cancer is regarded as a common fatal disease affecting humans throughout the entire world. Early diagnosis is vital to save the patient's life and Computed Tomography (CT) scans are referred to as the major imaging modes but, the manual examinat...
Computer methods and programs in biomedicine
Jan 25, 2025
BACKGROUND AND OBJECTIVES: Current state-of-the-art medical image segmentation methods prioritize precision but often at the expense of increased computational demands and larger model sizes. Applying these large-scale models to the relatively limite...
BACKGROUND: Early treatment discontinuation in substance use disorder treatment settings is common and often difficult to predict. We leveraged a machine learning approach (i.e., random forest) to identify individuals at risk for treatment attrition,...
Indigenous and local knowledge (ILK) is increasingly used along with scientific knowledge (SK) to understand climate change. The multi evidence base (MEB) offers ways of combining knowledge systems together. Nonetheless, there is little guidance on h...
Clinical risk prediction models are ubiquitous in many surgical domains. The traditional approach to develop these models involves the use of regression analysis. Machine learning algorithms are gaining in popularity as an alternative approach for pr...
BACKGROUND: Generalized Anxiety Disorder (GAD) is a chronic condition. Enabling the prediction of individual trajectories would facilitate tailored management approaches for these individuals. This study used machine learning techniques to predict th...
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