Individual Trip Destination Prediction aims to accurately forecast an individual's future travel destinations by analyzing their historical trajectory data, holding significant application value in intelligent navigation, personalized recommendations...
Aiming at the problems of blind sampling points and slow planning speed of path planning Rapidly-exploring Random Trees algorithm, an effective region sampling Levy Rapidly-exploring Random Trees algorithm (LRRT*) is proposed based on the improved Le...
Reinforcement learning (RL) has demonstrated significant potential in social robot autonomous navigation, yet existing research lacks in-depth discussion on the feasibility of navigation strategies. Therefore, this paper proposes an Integrated Decisi...
OBJECTIVE: The aim of this study was to automatically detect teeth with dens invaginatus (DI) in panoramic radiographs using deep learning algorithms and to compare the success of the algorithms.
BACKGROUND: Temporomandibular disorders (TMDs) are frequently associated with posterior condylar displacement; however, early prediction of this displacement remains a significant challenge. Therefore, in this study, we aimed to develop and evaluate ...
OBJECTIVE: To create an automated PET/CT segmentation method and radiomics model to forecast Mismatch repair (MMR) and TP53 gene expression in endometrial cancer patients, and to examine the effect of gene expression variability on image texture feat...
BACKGROUND AND OBJECTIVE: Stroke ranks among the leading causes of disability and death worldwide. Timely detection can reduce its impact. Machine learning delivers powerful tools for image‑based diagnosis. This study introduces StrokeNeXt, a lightwe...
BACKGROUND: Glioma is a common primary malignant brain tumor. This study aimed to develop a predictive model for glioma risk by these screened key SNPs in the Chinese Han population.
Deep learning enables the modelling of high-resolution histopathology whole-slide images (WSI). Weakly supervised learning of tile-level data is typically applied for tasks where labels only exist on the patient or WSI level (e.g. patient outcomes or...
In clinical medicine, a reliable and resource-friendly computer-aided diagnosis (CAD) method for brain tumor segmentation is essential to enhance diagnostic accuracy and therapeutic outcomes, particularly in regions with uneven healthcare resource di...
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