Accurate prediction of crash injury severity and understanding the seriousness of multi-classification injuries is vital for informing authorities and the public. This Knowledge is crucial for enhancing road safety and reducing congestion, as differe...
Artificial intelligence (Al) is transforming surgical care by enhancing risk prediction, preoperative planning, and surgical education. Unlike traditional statistical tools, Al-especially machine learning-can process complex, nonlinear clinical data ...
Anesthesiology and critical care medicine contain a vast repository of patient data that can be analyzed and decoded by artificial intelligence applications. Although there has been a rapid growth in the development of predictive analytics to improve...
INTRODUCTION: The role of non-suicidal self-injury (NSSI) in the suicide process of people with major depressive disorder(MDD) remains controversial. Therefore, the purpose of this study was to investigate the role NSSI plays in suicide risk in peopl...
Accurate prediction of stroke risk at an early stage is essential for timely intervention and prevention, especially given the serious health consequences and economic burden that strokes can cause. In this study, we proposed a class-balanced and dat...
To improve the effectiveness of diabetes risk prediction, this study proposes a novel method based on focal active learning strategies combined with machine learning models. Existing machine learning models often suffer from poor performance on imbal...
Accurate risk assessment in international trade settlement has become increasingly critical as global financial transactions grow in scale and complexity. This study proposes a hybrid model-Genetic Algorithm-optimized Fuzzy Neural Network (GA-FNN)-to...
Examining the cancer risk associated with oral groundwater (GW) intake is crucial, particularly in regions heavily reliant on GW for human consumption and agriculture. The study was based on real field investigations and controlled laboratory experim...
OBJECTIVES: To identify and characterise distinct subgroups of patients with asthma with severe acute exacerbations (AEs) by using a multistep clustering methodology that combines supervised and unsupervised machine learning.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 5, 2025
Assessing the preoperative malignancy risk of gastrointestinal stromal tumors (GISTs) is crucial for determining the appropriate treatment plan and prognosis. The current automated diagnosis of GISTs based on endoscopic ultrasound (EUS) pose challeng...
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