AIMC Topic: Algorithms

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Research and application of deep learning-based sleep staging: Data, modeling, validation, and clinical practice.

Sleep medicine reviews
Over the past few decades, researchers have attempted to simplify and accelerate the process of sleep stage classification through various approaches; however, only a few such approaches have gained widespread acceptance. Artificial intelligence tech...

Artificial intelligence-based speckle featurization and localization for ultrasound speckle tracking velocimetry.

Ultrasonics
Deep learning-based super-resolution ultrasound (DL-SRU) framework has been successful in improving spatial resolution and measuring the velocity field information of a blood flows by localizing and tracking speckle signals of red blood cells (RBCs) ...

Unsupervised SoftOtsuNet Augmentation for Clinical Dermatology Image Classifiers.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Data Augmentation is a crucial tool in the Machine Learning (ML) toolbox because it can extract novel, useful training images from an existing dataset, thereby improving accuracy and reducing overfitting in a Deep Neural Network (DNNs). However, clin...

Evaluating Deep Learning Performance for P300 Neural Signal Classification.

AMIA ... Annual Symposium proceedings. AMIA Symposium
P300 event-related potential (ERP) signals are useful neurological biomarkers, and their accurate classification is important when studying the cognitive functions in patients with neurological disorders. While many studies have proposed models for c...

Registration of preoperative temporal bone CT-scan to otoendoscopic video for augmented-reality based on convolutional neural networks.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: Patient-to-image registration is a preliminary step required in surgical navigation based on preoperative images. Human intervention and fiducial markers hamper this task as they are time-consuming and introduce potential errors. We aimed to...

Inter-fractional portability of deep learning models for lung target tracking on cine imaging acquired in MRI-guided radiotherapy.

Physical and engineering sciences in medicine
MRI-guided radiotherapy systems enable beam gating by tracking the target on planar, two-dimensional cine images acquired during treatment. This study aims to evaluate how deep-learning (DL) models for target tracking that are trained on data from on...

Sampling complex topology structures for spiking neural networks.

Neural networks : the official journal of the International Neural Network Society
Spiking Neural Networks (SNNs) have been considered a potential competitor to Artificial Neural Networks (ANNs) due to their high biological plausibility and energy efficiency. However, the architecture design of SNN has not been well studied. Previo...

End-to-end volumetric segmentation of white matter hyperintensities using deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Reliable detection of white matter hyperintensities (WMH) is crucial for studying the impact of diffuse white-matter pathology on brain health and monitoring changes in WMH load over time. However, manual annotation of 3D h...

Essential genes identification model based on sequence feature map and graph convolutional neural network.

BMC genomics
BACKGROUND: Essential genes encode functions that play a vital role in the life activities of organisms, encompassing growth, development, immune system functioning, and cell structure maintenance. Conventional experimental techniques for identifying...

The Three-Lead EEG Sensor: Introducing an EEG-Assisted Depression Diagnosis System Based on Ant Lion Optimization.

IEEE transactions on biomedical circuits and systems
For depression diagnosis, traditional methods such as interviews and clinical scales have been widely leveraged in the past few decades, but they are subjective, time-consuming, and labor-consuming. With the development of affective computing and Art...