AIMC Topic: Algorithms

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Detecting eavesdropping nodes in the power Internet of Things based on Kolmogorov-Arnold networks.

PloS one
The rapid proliferation of the Power Internet of Things (PIoT) has given rise to severe network security threats, with eavesdropping attacks emerging as a paramount concern. Traditional eavesdropping detection methods struggle to adapt to complex and...

Apnea detection using wrist actigraphy in patients with heterogeneous sleep disorders.

Scientific reports
Obstructive sleep apnea (OSA) and related hypoxia are well-established cardiovascular and neurocognitive risk factors. Current multi-sensor diagnostic approaches are intrusive and prone to misdiagnosis when simplified. This study introduces an enhanc...

An improved Red-billed blue magpie feature selection algorithm for medical data processing.

PloS one
Feature selection is a crucial preprocessing step in the fields of machine learning, data mining and pattern recognition. In medical data analysis, the large number and complexity of features are often accompanied by redundant or irrelevant features,...

EFCRFNet: A novel multi-scale framework for salient object detection.

PloS one
Salient Object Detection (SOD) is a fundamental task in computer vision, aiming to identify prominent regions within images. Traditional methods and deep learning-based models often encounter challenges in capturing crucial information in complex sce...

Preliminary Development of a Database for Detecting Active Mounting Behaviors Using Signals Acquired from IoT Collars in Free-Grazing Cattle.

Sensors (Basel, Switzerland)
This study presents the development of a database for detecting active mounts, utilizing IoT collars equipped with Inertial Measurement Units (IMUs) installed on eight Holstein Friesian cows, along with video recordings from a long-range PTZ camera m...

CoupleMDA: Metapath-Induced Structural-Semantic Coupling Network for miRNA-Disease Association Prediction.

International journal of molecular sciences
The prediction of microRNA-disease associations (MDAs) is crucial for understanding disease mechanisms and biomarker discovery. While graph neural networks have emerged as promising tools for MDA prediction, existing methods face critical limitations...

Computer Viewing Model for Classification of Erythrocytes Infected with spp. Applied to Malaria Diagnosis Using Optical Microscope.

Medicina (Kaunas, Lithuania)
Malaria is a disease that can result in a variety of complications. Diagnosis is carried out by an optical microscope and depends on operator experience. The use of artificial intelligence to identify morphological patterns in erythrocytes would imp...

Imbalanced feature generation based on bootstrap power spectral curve for estimating respiratory rate.

Scientific reports
Rapid respiratory rate (RR) changes in older adults may indicate serious illness. Therefore, accurately estimating RR for cardiorespiratory fitness is essential. However, machine learning algorithm-related errors are unsuitable for medical decision-m...

Non-invasive prediction of DCE-MRI radiomics model on CCR5 in breast cancer based on a machine learning algorithm.

Cancer biomarkers : section A of Disease markers
BackgroundNon-invasive methods with universal prognostic guidance for detecting breast cancer (BC) survival biomarkers need to be further explored.ObjectiveThis study aimed to investigate C-C motif chemokine receptor type 5 (CCR5) prognosis value in ...

Time-series visual representations for sleep stages classification.

PloS one
Polysomnography is the standard method for sleep stage classification; however, it is costly and requires controlled environments, which can disrupt natural sleep patterns. Smartwatches offer a practical, non-invasive, and cost-effective alternative ...