AIMC Topic: Deep Learning

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Vocal performance evaluation of the intelligent note recognition method based on deep learning.

Scientific reports
This study aims to optimize the ability of note recognition and improve the accuracy of vocal performance evaluation. Firstly, the basic theory of music is analyzed. Secondly, the convolutional neural network (CNN) in deep learning (DL) is selected t...

Revolutionizing Alzheimer's disease detection with a cutting-edge CAPCBAM deep learning framework.

Scientific reports
Early and accurate diagnosis of Alzheimer's disease (AD) is crucial for effective treatment. While the integration of deep learning techniques for AD classification is not entirely new, this study introduces CAPCBAM-a framework that extends prior app...

Frailty identification using a sensor-based upper-extremity function test: a deep learning approach.

Scientific reports
The global increase in the older adult population highlights the need for effective frailty assessment, a condition linked to adverse health outcomes such as hospitalization and mortality. Existing frailty assessment tools, like the Fried phenotype a...

Development of an Artificial Intelligence-Enabled Electrocardiography to Detect 23 Cardiac Arrhythmias and Predict Cardiovascular Outcomes.

Journal of medical systems
Arrhythmias are common and can affect individuals with or without structural heart disease. Deep learning models (DLMs) have shown the ability to recognize arrhythmias using 12-lead electrocardiograms (ECGs). However, the limited types of arrhythmias...

A novel deep learning approach to classify 3D foot types of diabetic patients.

Scientific reports
Diabetes mellitus is a worldwide epidemic that leads to significant changes in foot shape, deformities, and ulcers. Precise classification of diabetic foot not only helps identify foot abnormalities but also facilitates personalized treatment and pre...

Reinforcement learning-driven automated head and neck simultaneous integrated boost (SIB) radiation therapy: flexible treatment planning aligned with clinical preferences.

Physics in medicine and biology
Head-and-neck simultaneous integrated boost (SIB) treatment planning using intensity modulated radiation therapy is particularly challenging due to the proximity to organs-at-risk. Depending on the specific clinical conditions, different parotid-spar...

An end-to-end neural network for 4D cardiac CT reconstruction using single-beat scans.

Physics in medicine and biology
Motion artifacts remain a significant challenge in cardiac CT imaging, often impairing the accurate detection and diagnosis of cardiac diseases. These artifacts result from involuntary cardiac motion, and traditional mitigation methods typically rely...

A machine learning toolkit assisted approach for IMRT fluence map optimization: feasibility and advantages.

Biomedical physics & engineering express
. Traditional machine learning (ML) and deep learning (DL) applications in treatment planning rely on complex model architectures and large, high-quality training datasets. However, they cannot fully replace the conventional optimization process. Thi...

Advancing Single-Plane Wave Ultrasound Imaging With Implicit Multiangle Acoustic Synthesis via Deep Learning.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Plane wave imaging (PWI) is pivotal in medical ultrasound (US), prized for its ultrafast capabilities essential for real-time physiological monitoring. Traditionally, enhancing image quality in PWI has necessitated an increase in the number of plane ...

Tissue Clutter Filtering Methods in Ultrasound Localization Microscopy Based on Complex-Valued Networks and Knowledge Distillation.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Ultrasound localization microscopy (ULM) is a blood flow imaging technique that utilizes micrometer-sized microbubbles (MBs) as contrast agents to achieve high-resolution microvessel reconstruction through precise localization and tracking of MBs. Th...