Humanoid robots are typically designed for static environments, but real-world applications demand robust performance under dynamic, uncertain conditions. This paper introduces a perceptive motion planning and control algorithm that enables humanoid ...
OBJECTIVE: Recognizing glomerular lesions is essential in diagnosing chronic kidney disease. However, deep learning faces challenges due to the lesion heterogeneity, superposition, progression, and tissue incompleteness, leading to uncertainty in mod...
In this paper, we introduce a novel concordance-based predictive uncertainty (CPU)-Index, which integrates insights from subgroup analysis and personalized AI time-to-event models. Through its application in refining lung cancer screening (LCS) predi...
Neural networks : the official journal of the International Neural Network Society
39721102
Neural networks have significant advantages in the estimation of uncertainty dynamics, which can afford highly accurate prediction outcomes and enhance control robustness. With this in mind, this study presents a neural network-based method to invest...
Inability to express the confidence level and detect unseen disease classes limits the clinical implementation of artificial intelligence in the real world. We develop a foundation model with uncertainty estimation (FMUE) to detect 16 retinal conditi...
BMC medical informatics and decision making
39695672
BACKGROUND: [F] Fluorodeoxyglucose (FDG) PET-CT is a clinical imaging modality widely used in diagnosing and staging lung cancer. The clinical findings of PET-CT studies are contained within free text reports, which can currently only be categorised ...
International journal of molecular sciences
39684785
Mass spectral identification (in particular, in metabolomics) can be refined by comparing the observed and predicted properties of molecules, such as chromatographic retention. Significant advancements have been made in predicting these values using ...
This study investigates the combined impact of artificial intelligence (AI) tools and Uncertain Motivation (UM) strategies on the argumentative writing performance of Saudi EFL learners, using the Toulmin Model. Sixty Saudi EFL students participated ...
Deep learning-based image segmentation has allowed for the fully automated, accurate, and rapid analysis of musculoskeletal (MSK) structures from medical images. However, current approaches were either applied only to 2D cross-sectional images, addre...
The burgeoning progress of cutting-edge technology paradoxically evokes nostalgia. How does this emotion influence responses to innovative technology, such as Artificial Intelligence (AI)? We hypothesized that two pathways operate concurrently. First...