AIMC Topic: Algorithms

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Topology-Guided Graph Masked Autoencoder Learning for Population-Based Neurodevelopmental Disorder Diagnosis.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Exploring the pathogenic mechanisms of brain disorders within population is an important research in the field of neuroscience. Existing methods either combine clinical information to assist analysis or use data augmentation for sample expansion, ign...

SMANet: A Model Combining SincNet, Multi-Branch Spatial-Temporal CNN, and Attention Mechanism for Motor Imagery BCI.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Building a brain-computer interface (BCI) based on motor imagery (MI) requires accurately decoding MI tasks, which poses a significant challenge due to individual discrepancy among subjects and low signal-to-noise ratio of EEG signals. We propose an ...

VTrans: A VAE-Based Pre-Trained Transformer Method for Microbiome Data Analysis.

Journal of computational biology : a journal of computational molecular cell biology
Predicting the survival outcomes and assessing the risk of patients play a pivotal role in comprehending the microbial composition across various stages of cancer. With the ongoing advancements in deep learning, it has been substantiated that deep le...

S-Net: Learning spectral-spatio self-similarity for hyperspectral image super-resolution.

Neural networks : the official journal of the International Neural Network Society
As an economically feasible approach for hyperspectral image (HSI) super-resolution, fusing HSI with multispectral image (MSI) utilizes the complementary nature of cross-modality information. Given the common presence of repetitive textures and struc...

MSCViT: A small-size ViT architecture with multi-scale self-attention mechanism for tiny datasets.

Neural networks : the official journal of the International Neural Network Society
Vision Transformer (ViT) has demonstrated significant potential in various vision tasks due to its strong ability in modeling long-range dependencies. However, such success is largely fueled by training on massive samples. In real applications, the l...

Integrating prior knowledge with deep learning for optimized quality control in corneal images: A multicenter study.

Computer methods and programs in biomedicine
OBJECTIVE: Artificial intelligence (AI) models are effective for analyzing high-quality slit-lamp images but often face challenges in real-world clinical settings due to image variability. This study aims to develop and evaluate a hybrid AI-based ima...

Structural uncertainty estimation for medical image segmentation.

Medical image analysis
Precise segmentation and uncertainty estimation are crucial for error identification and correction in medical diagnostic assistance. Existing methods mainly rely on pixel-wise uncertainty estimations. They (1) neglect the global context, leading to ...

Challenges, optimization strategies, and future horizons of advanced deep learning approaches for brain lesion segmentation.

Methods (San Diego, Calif.)
Brain lesion segmentation is challenging in medical image analysis, aiming to delineate lesion regions precisely. Deep learning (DL) techniques have recently demonstrated promising results across various computer vision tasks, including semantic segm...

A Deep Learning Approach for Nerve Injury Classification in Brachial Plexopathies Using Magnetic Resonance Neurography with Modified Hiking Optimization Algorithm.

Academic radiology
RATIONALE AND OBJECTIVES: Brachial plexopathies (BPs) encompass a complex spectrum of nerve injuries affecting motor and sensory function in the upper extremities. Diagnosis is challenging due to the intricate anatomy and symptom overlap with other n...

Impact of fine-tuning parameters of convolutional neural network for skin cancer detection.

Scientific reports
Melanoma skin cancer is a deadly disease with a high mortality rate. A prompt diagnosis can aid in the treatment of the disease and potentially save the patient's life. Artificial intelligence methods can help diagnose cancer at a rapid speed. The li...