AIMC Topic: Neural Networks, Computer

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Developing an innovative lung cancer detection model for accurate diagnosis in AI healthcare systems.

Scientific reports
Accurate Lung cancer (LC) identification is a big medical problem in the AI-based healthcare systems. Various deep learning-based methods have been proposed for Lung cancer diagnosis. In this study, we proposed a Deep learning techniques-based integr...

Few-shot network intrusion detection method based on multi-domain fusion and cross-attention.

PloS one
Deep learning methods have achieved remarkable progress in network intrusion detection. However, their performance often deteriorates significantly in real-world scenarios characterized by limited attack samples and substantial domain shifts. To addr...

Towards real-world monitoring scenarios: An improved point prediction method for crowd counting based on contrastive learning.

PloS one
In open environments, complex and variable backgrounds and dense multi-scale targets are two key challenges for crowd counting. Due to the reliance on supervised learning with labeled data, current methods struggle to adapt to crowd detection in comp...

Enhancing IDS for the IoMT based on advanced features selection and deep learning methods to increase the model trustworthiness.

PloS one
Information technology has significantly impacted society. IoT and its specialized variant, IoMT, enable remote patient monitoring and improve healthcare. While it contributes to improving healthcare services, it may pose significant security challen...

Posture prediction models in digital human modeling for ergonomic design: A systematic review.

Medical engineering & physics
Posture prediction models have been widely used to support ergonomic design. This systematic review critically assessed the development, validation, and applications of posture prediction models in Digital Human Modeling (DHM). Following PRISMA guide...

Cephalometric landmark detection using vision transformers with direct coordinate prediction.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
Cephalometric Landmark Detection (CLD), i.e. annotating interest points in lateral X-ray images, is the crucial first step of every orthodontic therapy. While CLD has immense potential for automation using Deep Learning methods, carefully crafted con...

A deep learning model combining convolutional neural networks and a selective kernel mechanism for SSVEP-Based BCIs.

Computers in biology and medicine
Existing deep learning methods for brain-computer interfaces (BCIs) based on steady-state visually evoked potential (SSVEP) face several challenges, such as overfitting when training data are insufficient, and the difficulty of effectively capturing ...

Real-Time Detection of Trace Breath Isoprene Based on Circular Domain Spectral Reconstruction Filtering Combined with Convolutional Neural Network.

Analytical chemistry
The detection of trace isoprene in breath provides a noninvasive method for lung cancer diagnosis. However, the presence of interfering components and the parts per billion (ppb) concentration levels of isoprene in breath complicate detection. In thi...

stGRL: spatial domain identification, denoising, and imputation algorithm for spatial transcriptome data based on multi-task graph contrastive representation learning.

BMC biology
BACKGROUND: Spatial transcriptomics now enables sequencing while preserving the spatial location of cells. This significantly enhances researchers' understanding of cellular and tissue functions in their spatial context. However, due to current techn...