AIMC Topic: Algorithms

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[A coronary artery plaque segmentation method based on focal weighted accuracy loss function].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Medical images of coronary artery plaque are always accompanied by the situation of extreme class imbalance. The traditional two-step methods locate the region of interest (ROI) in the sample firstly, and then segment the sample within the ROI. On th...

[Automatic detection and visualization of myocardial infarction in electrocardiograms based on an interpretable deep learning model].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Automated detection of myocardial infarction (MI) is crucial for preventing sudden cardiac death and enabling early intervention in cardiovascular diseases. This paper proposes a deep learning framework based on a lightweight convolutional neural net...

[A motor imagery decoding study integrating differential attention with a multi-scale adaptive temporal convolutional network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Motor imagery electroencephalogram (MI-EEG) decoding algorithms face multiple challenges. These include incomplete feature extraction, susceptibility of attention mechanisms to distraction under low signal-to-noise ratios, and limited capture of long...

Artifact-robust Deep Learning-based Segmentation of 3D Phase-contrast MR Angiography: A Novel Data Augmentation Approach.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
This study presents a novel data augmentation approach to improve deep learning (DL)-based segmentation for 3D phase-contrast magnetic resonance angiography (PC-MRA) images affected by pulsation artifacts. Augmentation was achieved by simulating puls...

Using Machine Learning Algorithms to Identify Key Predictors of Invasive Mold Infection Surveillance.

The Journal of infectious diseases
BACKGROUND: Invasive mold infections (IMI) can lead to severe morbidity and mortality, but routine public health surveillance is lacking. Although extensive evaluation is needed for clinical diagnosis, case classification prediction models may inform...

Evaluation of Bio-Inspired Models under Different Learning Settings for Energy Efficiency in Network Traffic Prediction.

International journal of neural systems
Cellular traffic forecasting is a critical task that enables network operators to efficiently allocate resources and address anomalies in rapidly evolving environments. The exponential growth of data collected from base stations poses significant cha...

Hyperspectral imaging and machine learning for quality assessment of apples with different bagging types.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
This study examined how different bagging types (unbagged, mesh-bagged, and paper-bagged) affect the internal and external quality of fruits. Spectral images of 307 apples were collected using a visible-near infrared hyperspectral imaging system, and...

Artificial intelligence-based identification of thin-cap fibroatheromas and clinical outcomes: the PECTUS-AI study.

European heart journal
BACKGROUND AND AIMS: Coronary thin-cap fibroatheromas (TCFA) are associated with adverse outcome, but identification of TCFA requires expertise and is highly time-demanding. This study evaluated the utility of artificial intelligence (AI) for TCFA id...

Diagnosis of uterine diseases by label-free serum SERS fingerprints with machine learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Early detection of uterine diseases is critically important for women's reproductive health. Here, we propose a novel and robust serum-based SERS analysis platform that integrates machine learning algorithms. This is the first application of it in th...

The research on artificial intelligence-based Deer Velvet Antler traceability model based on emergent data features.

Talanta
Deer velvet antler(DVA) is highly valued for its nutritional properties, but its complex origins and widespread adulteration in the market have led to significant quality discrepancies. Therefore, this study aims to establish an efficient and accurat...