AIMC Topic: Algorithms

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A GA-stacking ensemble approach for forecasting energy consumption in a smart household: A comparative study of ensemble methods.

Journal of environmental management
The considerable amount of energy utilized by buildings has led to various environmental challenges that adversely impact human existence. Predicting buildings' energy usage is commonly acknowledged as encouraging energy efficiency and enabling well-...

DCRELM: dual correlation reduction network-based extreme learning machine for single-cell RNA-seq data clustering.

Scientific reports
Single-cell ribonucleic acid sequencing (scRNA-seq) is a high-throughput genomic technique that is utilized to investigate single-cell transcriptomes. Cluster analysis can effectively reveal the heterogeneity and diversity of cells in scRNA-seq data,...

Machine Learning-Aided Decision-Making Model for the Discontinuation of Continuous Renal Replacement Therapy.

Blood purification
INTRODUCTION: Continuous renal replacement therapy (CRRT) is a primary form of renal support for patients with acute kidney injury in an intensive care unit. Making an accurate decision of discontinuation is crucial for the prognosis of patients. Pre...

Application of an ensemble CatBoost model over complex dataset for vehicle classification.

PloS one
The classification of vehicles presents notable challenges within the domain of image processing. Traditional models suffer from inefficiency, prolonged training times for datasets, intricate feature extraction, and variable assignment complexities f...

Individual Prediction of Electric Field Induced by Deep-Brain Magnetic Stimulation With CNN-Transformer.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Deep-brain Magnetic Stimulation (DMS) can improve the symptoms caused by Alzheimer's disease by inducing rhythmic electric field in the deep brain, and the induced electric field is rhythm-dependent. However, calculating the induced electric field re...

Dual-input robust diagnostics for railway point machines via audio signals.

Network (Bristol, England)
Railway Point Machine (RPM) is a fundamental component of railway infrastructure and plays a crucial role in ensuring the safe operation of trains. Its primary function is to divert trains from one track to another, enabling connections between diffe...

Prediction of additional hospital days in patients undergoing cervical spine surgery with machine learning methods.

Computer assisted surgery (Abingdon, England)
BACKGROUND: Machine learning (ML), a subset of artificial intelligence (AI), uses algorithms to analyze data and predict outcomes without extensive human intervention. In healthcare, ML is gaining attention for enhancing patient outcomes. This study ...

Intelligent alert system for predicting invasive mechanical ventilation needs via noninvasive parameters: employing an integrated machine learning method with integration of multicenter databases.

Medical & biological engineering & computing
The use of invasive mechanical ventilation (IMV) is crucial in rescuing patients with respiratory dysfunction. Accurately predicting the demand for IMV is vital for clinical decision-making. However, current techniques are invasive and challenging to...

Advancing neural network calibration: The role of gradient decay in large-margin Softmax optimization.

Neural networks : the official journal of the International Neural Network Society
This study introduces a novel hyperparameter in the Softmax function to regulate the rate of gradient decay, which is dependent on sample probability. Our theoretical and empirical analyses reveal that both model generalization and calibration are si...

Accurate classification of glomerular diseases by hyperspectral imaging and transformer.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In renal disease research, precise glomerular disease diagnosis is crucial for treatment and prognosis. Currently reliant on invasive biopsies, this method bears risks and pathologist-dependent variability, yielding inconsis...