AIMC Topic: Algorithms

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Cross-ViT based benign and malignant classification of pulmonary nodules.

PloS one
The benign and malignant discrimination of pulmonary nodules plays a very important role in diagnosing the extent of lung cancer lesions. There are many methods using Convolutional neural network (CNN) for benign and malignant classification of pulmo...

Enhanced crayfish optimization algorithm: Orthogonal refracted opposition-based learning for robotic arm trajectory planning.

PloS one
In high-dimensional scenarios, trajectory planning is a challenging and computationally complex optimization task that requires finding the optimal trajectory within a complex domain. Metaheuristic (MH) algorithms provide a practical approach to solv...

Breast cancer image classification based on H&E staining using a causal attention graph neural network model.

Medical & biological engineering & computing
Breast cancer image classification remains a challenging task due to the high-resolution nature of pathological images and their complex feature distributions. Graph neural networks (GNNs) offer promising capabilities to capture local structural info...

Multi-source sparse broad transfer learning for parkinson's disease diagnosis via speech.

Medical & biological engineering & computing
Diagnosing Parkinson's disease (PD) via speech is crucial for its non-invasive and convenient data collection. However, the small sample size of PD speech data impedes accurate recognition of PD speech. Therefore, we propose a novel multi-source spar...

TF-BERT: Tensor-based fusion BERT for multimodal sentiment analysis.

Neural networks : the official journal of the International Neural Network Society
Multimodal Sentiment Analysis (MSA) has gained significant attention due to the limitations of unimodal sentiment recognition in complex real-world applications. Traditional approaches typically focus on using the Transformer for fusion. However, the...

Fast finite-time quantized control of multi-layer networks and its applications in secure communication.

Neural networks : the official journal of the International Neural Network Society
This paper introduces a quantized controller to address the challenge of fast finite-time synchronization of multi-layer networks, where each layer represents a distinct type of interaction within complex systems. Firstly, based on the stability theo...

RotInv-PCT: Rotation-Invariant Point Cloud Transformer via feature separation and aggregation.

Neural networks : the official journal of the International Neural Network Society
The widespread use of point clouds has spurred the rapid development of neural networks for point cloud processing. A crucial property of these networks is maintaining consistent output results under random rotations of the input point cloud, namely,...

Emotional stimulated speech-based assisted early diagnosis of depressive disorders using personality-enhanced deep learning.

Journal of affective disorders
BACKGROUND: Early diagnosis of depression is crucial, and speech-based early diagnosis of depression is promising, but insufficient data and lack of theoretical support make it difficult to be applied. Therefore, it is valuable to combine psychiatric...

Quantification of tissue stiffness with magnetic resonance elastography and finite difference time domain (FDTD) simulation-based spatiotemporal neural network.

Magnetic resonance imaging
Quantification of tissue stiffness with magnetic resonance elastography (MRE) is an inverse problem that is sensitive to noise. Conventional methods for the purpose include direct inversion (DI) and local frequency estimation (LFE). In this study, we...

Learning Phenotype Associated Signature in Spatial Transcriptomics with PASSAGE.

Small methods
Spatially resolved transcriptomics (SRT) is poised to advance the understanding of cellular organization within complex tissues under various physiological and pathological conditions at unprecedented resolution. Despite the development of numerous c...