AI Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

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Deep learning models for segmenting phonocardiogram signals: a comparative study.

PloS one
Cardiac auscultation requires the mechanical vibrations occurring on the body's surface, which carries a range of sound frequencies. These sounds are generated by the movement and pulsation of different cardiac structures as they facilitate blood cir...

c-Triadem: A constrained, explainable deep learning model to identify novel biomarkers in Alzheimer's disease.

PloS one
Alzheimer's disease (AD) is a neurodegenerative disorder that requires early diagnosis for effective management. However, issues with currently available diagnostic biomarkers preclude early diagnosis, necessitating the development of alternative bio...

CWMS-GAN: A small-sample bearing fault diagnosis method based on continuous wavelet transform and multi-size kernel attention mechanism.

PloS one
In industrial production, obtaining sufficient bearing fault signals is often extremely difficult, leading to a significant degradation in the performance of traditional deep learning-based fault diagnosis models. Many recent studies have shown that ...

A deep learning-based approach for the detection of cucumber diseases.

PloS one
Cucumbers play a significant role as a greenhouse crop globally. In numerous countries, they are fundamental to dietary practices, contributing significantly to the nutritional patterns of various populations. Due to unfavorable environmental conditi...

Assessing the cardioprotective effects of exercise in APOE mouse models using deep learning and photon-counting micro-CT.

PloS one
BACKGROUND: The allelic variations of the apolipoprotein E (APOE) gene play a critical role in regulating lipid metabolism and significantly impact cardiovascular disease risk (CVD). This study aimed to evaluate the impact of exercise on cardiac stru...

Optimizing CNN for pavement distress detection via edge-enhanced multi-scale feature fusion.

PloS one
Traditional crack detection methods initially relied on manual observation, followed by instrument-assisted techniques. Today, road surface inspection leverages deep learning to achieve automated crack detection. However, in the domain of deep learni...

A knowledge tracing approach with dual graph convolutional networks and positive/negative feature enhancement network.

PloS one
Knowledge tracing models predict students' mastery of specific knowledge points by analyzing their historical learning performance. However, existing methods struggle with handling a large number of skills, data sparsity, learning differences, and co...

Global burden and future trends of head and neck cancer: a deep learning-based analysis (1980-2030).

PloS one
BACKGROUND: Head and neck cancer (HNC) becomes a vital global health burden. Accurate assessment of the disease burden plays an essential role in setting health priorities and guiding decision-making.

Deep learning-based improved side-channel attacks using data denoising and feature fusion.

PloS one
Deep learning, as a high-performance data analysis method, has demonstrated superior efficiency and accuracy in side-channel attacks compared to traditional methods. However, many existing models enhance accuracy by stacking network layers, leading t...