AIMC Topic: Humans

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BioSAM: Generating SAM Prompts From Superpixel Graph for Biological Instance Segmentation.

IEEE journal of biomedical and health informatics
Proposal-free instance segmentation methods have significantly advanced the field of biological image analysis. Recently, the Segment Anything Model (SAM) has shown an extraordinary ability to handle challenging instance boundaries. However, directly...

Fine-Grained Fidgety Movement Classification Using Active Learning.

IEEE journal of biomedical and health informatics
Typically developing infants, between the corrected age of 9-20 weeks, produce fidgety movements. These movements can be identified with the General Movement Assessment, but their identification requires trained professionals to conduct the assessmen...

DCTP-Net: Dual-Branch CLIP-Enhance Textual Prompt-Aware Network for Acute Ischemic Stroke Lesion Segmentation From CT Image.

IEEE journal of biomedical and health informatics
Detecting early ischemic lesions (EIL) in computed tomography (CT) images is crucial for reducing diagnostic time and minimizing neuron loss due to oxygen deprivation. This paper introduces DCTP-Net, a dual-branch network for segmenting acute ischemi...

Spherical Harmonics-Based Deep Learning Achieves Generalized and Accurate Diffusion Tensor Imaging.

IEEE journal of biomedical and health informatics
Diffusion tensor imaging (DTI) is a prevalent magnetic resonance imaging (MRI) technique, widely used in clinical and neuroscience research. However, the reliability of DTI is affected by the low signal-to-noise ratio inherent in diffusion-weighted (...

Multiscale Spatial-Temporal Feature Fusion Neural Network for Motor Imagery Brain-Computer Interfaces.

IEEE journal of biomedical and health informatics
Motor imagery, one of the main brain-computer interface (BCI) paradigms, has been extensively utilized in numerous BCI applications, such as the interaction between disabled people and external devices. Precise decoding, one of the most significant a...

Step Width Estimation in Individuals With and Without Neurodegenerative Disease via a Novel Data-Augmentation Deep Learning Model and Minimal Wearable Inertial Sensors.

IEEE journal of biomedical and health informatics
Step width is vital for gait stability, postural balance control, and fall risk reduction. However, estimating step width typically requires either fixed cameras or a full kinematic body suit of wearable inertial measurement units (IMUs), both of whi...

Adversarial Exposure Attack on Diabetic Retinopathy Imagery Grading.

IEEE journal of biomedical and health informatics
Diabetic Retinopathy (DR) is a leading cause of vision loss around the world. To help diagnose it, numerous cutting-edge works have built powerful deep neural networks (DNNs) to automatically grade DR via retinal fundus images (RFIs). However, RFIs a...

Fuzzy Synchronization Likelihood Graph in Deep Neural Networks for Human Motion Time Series Analysis.

IEEE journal of biomedical and health informatics
Variable interactivity is crucial in biological multivariate time series analysis. This research suggests using graph structures to represent such interactions for more explainable decision-making processes. However, measuring the variable interactio...

Spatial Craving Patterns in Marijuana Users: Insights From fMRI Brain Connectivity Analysis With High-Order Graph Attention Neural Networks.

IEEE journal of biomedical and health informatics
The excessive consumption of marijuana can induce substantial psychological and social consequences. In this investigation, we propose an elucidative framework termed high-order graph attention neural networks (HOGANN) for the classification of Marij...

Self-Supervised Contrastive Learning on Attribute and Topology Graphs for Predicting Relationships Among lncRNAs, miRNAs and Diseases.

IEEE journal of biomedical and health informatics
Exploring associations between long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and diseases is crucial for disease prevention, diagnosis and treatment. While determining these relationships experimentally is resource-intensive and time-consuming, ...