AIMC Topic: Algorithms

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Early detection of paroxysmal atrial fibrillation from non-episodic ECG data using cardiac dynamics features and different classification models.

Biomedical physics & engineering express
Intelligent computer-aided diagnosis techniques enable inspection of invisible electrocardiogram (ECG) pathological changes for early detection of latent heart diseases. This study concentrates on latent pathological changes within non-episodic ECG d...

gSelformer-MV: Multiview, Subgraph-Augmented Group SELFIES Transformer for Molecular Property Prediction.

Journal of chemical information and modeling
Data-driven approaches are essential for relating properties to the chemical structure. Atom-focused views of individual compounds are common in molecular representation learning: graph neural networks and chemical language models, the two main algor...

Establishment of a postoperative delirium risk prediction model for elderly hip fracture patients based on machine learning algorithms.

BMC geriatrics
BACKGROUND: Although no definitive treatment exists, 30-40% of postoperative delirium cases are preventable through early risk identification and intervention. Therefore our aim was to develop and evaluate a postoperative delirium risk prediction mod...

Pattern and structural detection in grayscale images through the application of quantile graphs in higher-dimensional spaces.

Scientific reports
Deep Learning (DL) and Machine Learning (ML) algorithms are adept at managing and classifying a wide range of data formats, including time series, text, and images, addressing challenges in both supervised and unsupervised learning. However, the prac...

An augmented preference-based Bayesian approach for optimizing neuromodulation stimulation parameters using meta learning.

Journal of neural engineering
Electrical neuromodulation is increasingly used in the treatment of neurological disorders; however, the selection of stimulation parameters that provide optimal therapeutic benefits remains a major challenge. Moreover, identifying pathological bioma...

Construction of an intelligent screening model for allergic rhinitis based on routine blood tests.

PloS one
The incidence of allergic rhinitis (AR) has been increasing annually, severely impacting patients' quality of life and increasing socioeconomic burdens. The limitations of current diagnostic methods have made the development of efficient, low-cost ea...

Brand public opinion data analysis method based on deep learning.

PloS one
With the rapid development of Internet information technology and digital technology, various network platforms and media are showing a vigorous growth momentum. The powerful power of online public opinion has an immeasurable impact on brand awarenes...

Development of a rapid detection method for patch thickness based on machine vision and near infrared spectroscopy: a case study of curcumin patch.

International journal of pharmaceutics
Patches represent a significant dosage form within transdermal drug delivery systems. In the quality control of transdermal patches, thickness not only affects the drug loading per unit area and drug release behavior but also is associated with patie...

Machine Learning in Microbiome Research and Engineering.

ACS synthetic biology
Microbiomes, complex communities of microorganisms and their genetic material, hold immense potential for addressing global challenges in diverse sectors, including healthcare, agriculture, and bioproduction. Engineering these intricate ecosystems, h...

Optimizing intervertebral disc cell metabolic phenotyping with machine learning and artificial neural networks.

Scientific reports
Biological phenotyping of cellular metabolism is essential for deciphering health and disease states. The Seahorse XF analyzer enables direct measurement of oxygen consumption rate (OCR) and extracellular acidification rate (ECAR), providing insight ...