AIMC Topic: Algorithms

Clear Filters Showing 2091 to 2100 of 28713 articles

GRLGRN: graph representation-based learning to infer gene regulatory networks from single-cell RNA-seq data.

BMC bioinformatics
BACKGROUND: A gene regulatory network (GRN) is a graph-level representation that describes the regulatory relationships between transcription factors and target genes in cells. The reconstruction of GRNs can help investigate cellular dynamics, drug d...

AI analysis for ejection fraction estimation from 12-lead ECG.

Scientific reports
Heart failure (HF) remains a leading global cause of cardiovascular deaths, with its prevalence expected to rise in the upcoming decade. Measuring the heart ejection fraction (EF) is crucial for diagnosing and monitoring HF. Although echocardiography...

DrugGen enhances drug discovery with large language models and reinforcement learning.

Scientific reports
Traditional drug design faces significant challenges due to inherent chemical and biological complexities, often resulting in high failure rates in clinical trials. Deep learning advancements, particularly generative models, offer potential solutions...

Comparative analysis of heart disease prediction using logistic regression, SVM, KNN, and random forest with cross-validation for improved accuracy.

Scientific reports
This primary research paper emphasizes cross-validation, where data samples are reshuffled in each iteration to form randomized subsets divided into n folds. This method improves model performance and achieves higher accuracy than the baseline model....

Daily Automated Prediction of Delirium Risk in Hospitalized Patients: Model Development and Validation.

JMIR medical informatics
BACKGROUND: Delirium is common in hospitalized patients and is correlated with increased morbidity and mortality. Despite this, delirium is underdiagnosed, and many institutions do not have sufficient resources to consistently apply effective screeni...

Convolutional Neural Network approach to classify mitochondrial morphologies.

Computational biology and chemistry
The morphology of the mitochondrial network is a major indicator of cellular health and function, with changes often linked to various physiological and pathological conditions. As a result, efficient methods to quickly assess mitochondrial shape in ...

Deep learning algorithms to assist in imaging diagnosis in individuals with disc herniation or spondylolisthesis: A scoping review.

International journal of medical informatics
BACKGROUND: Deep learning applications in medical imaging have advanced significantly, supporting the diagnosis of spinal disorders such as disc herniation and spondylolisthesis. This study aimed to review deep learning algorithms used in diagnostic ...

Unraveling almonds deterioration using whole-cell biosensor coupled with machine learning approaches and SHAP interpretation.

Food chemistry
As almonds are prone to oxidation during storage, it is essential to construct a real-time method to monitor the quality of almonds efficiently. In this study, the in situ detection was developed using whole-cell biosensor combined with machine learn...

Adaptive token selection for scalable point cloud transformers.

Neural networks : the official journal of the International Neural Network Society
The recent surge in 3D data acquisition has spurred the development of geometric deep learning models for point cloud processing, boosted by the remarkable success of transformers in natural language processing. While point cloud transformers (PTs) h...

Multiscroll hidden attractor in memristive autapse neuron model and its memristor-based scroll control and application in image encryption.

Neural networks : the official journal of the International Neural Network Society
In current neurodynamic studies, memristor models using polynomial or multiple nested composite functions are primarily employed to generate multiscroll attractors, but their complex mathematical form restricts both research and application. To addre...