AIMC Topic: Algorithms

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Off-Body Sleep Analysis for Predicting Adverse Behavior in Individuals With Autism Spectrum Disorder.

IEEE journal of biomedical and health informatics
Poor sleep quality in Autism Spectrum Disorder (ASD) individuals is linked to severe daytime behaviors. This study explores the relationship between a prior night's sleep structure and its predictive power for next-day behavior in ASD individuals. Th...

Classification of Multi-Parametric Body MRI Series Using Deep Learning.

IEEE journal of biomedical and health informatics
Multi-parametric magnetic resonance imaging (mpMRI) exams have various series types acquired with different imaging protocols. The DICOM headers of these series often have incorrect information due to the sheer diversity of protocols and occasional t...

Modeling Functional Brain Networks for ADHD via Spatial Preservation-Based Neural Architecture Search.

IEEE journal of biomedical and health informatics
Modeling functional brain networks (FBNs) for attention deficit hyperactivity disorder (ADHD) has sparked significant interest since the abnormal functional connectivity is discovered in certain functional magnetic resonance imaging (fMRI)-based brai...

Framework for Deep Learning Based Multi-Modality Image Registration of Snapshot and Pathology Images.

IEEE journal of biomedical and health informatics
Multi-modality image registration is an important task in medical imaging because it allows for information from different domains to be correlated. Histopathology plays a crucial role in oncologic surgery as it is the gold standard for investigating...

GKE-TUNet: Geometry-Knowledge Embedded TransUNet Model for Retinal Vessel Segmentation Considering Anatomical Topology.

IEEE journal of biomedical and health informatics
Automated retinal vessel segmentation is crucial for computer-aided clinical diagnosis and retinopathy screening. However, deep learning faces challenges in extracting complex intertwined structures and subtle small vessels from densely vascularized ...

Drug-Target Prediction Based on Dynamic Heterogeneous Graph Convolutional Network.

IEEE journal of biomedical and health informatics
Novel drug-target interaction (DTI) prediction is crucial in drug discovery and repositioning. Recently, graph neural network (GNN) has shown promising results in identifying DTI by using thresholds to construct heterogeneous graphs. However, an empi...

A General DNA-Like Hybrid Symbiosis Framework: An EEG Cognitive Recognition Method.

IEEE journal of biomedical and health informatics
In electroencephalogram (EEG) cognitive recognition research, the combined use of artificial neural networks (ANNs) and spiking neural networks (SNNs) plays an important role to realize different categories of recognition tasks. However, most of the ...

Generating Biomedical Hypothesis With Spatiotemporal Transformers.

IEEE journal of biomedical and health informatics
Generating biomedical hypotheses is a difficult task as it requires uncovering the implicit associations between massive scientific terms from a large body of published literature. A recent line of Hypothesis Generation (HG) approaches - temporal gra...

Characterizing the Contribution of Dependent Features in XAI Methods.

IEEE journal of biomedical and health informatics
Explainable Artificial Intelligence (XAI) provides tools to help understanding how AI models work and reach a particular decision or outcome. It helps to increase the interpretability of models and makes them more trustworthy and transparent. In this...

Uncertainty-Aware Health Diagnostics via Class-Balanced Evidential Deep Learning.

IEEE journal of biomedical and health informatics
Uncertainty quantification is critical for ensuring the safety of deep learning-enabled health diagnostics, as it helps the model account for unknown factors and reduces the risk of misdiagnosis. However, existing uncertainty quantification studies o...