AIMC Topic: Algorithms

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MTSA-SC: A multi-task learning approach for individual trip destination prediction with multi-trajectory subsequence alignment and space-aware loss functions.

PloS one
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...

LRRT*: A robotic arm path planning algorithm based on an improved Levy flight strategy with effective region sampling RRT.

PloS one
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...

Integrated decision-control for social robot autonomous navigation considering nonlinear dynamics model.

PloS one
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...

Artificial intelligence-based detection of dens invaginatus in panoramic radiographs.

BMC oral health
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.

A radiogenomics study on F-FDG PET/CT in endometrial cancer by a novel deep learning segmentation algorithm.

BMC cancer
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...

StrokeNeXt: an automated stroke classification model using computed tomography and magnetic resonance images.

BMC medical imaging
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...

Screening of glioma susceptibility SNPs and construction of risk models based on machine learning algorithms.

BMC neurology
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.

A method for spatial interpretation of weakly supervised deep learning models in computational pathology.

Scientific reports
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...

A 3D lightweight network with Roberts edge enhancement model (LR-Net) for brain tumor segmentation.

Scientific reports
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...