AIMC Topic: Machine Learning

Clear Filters Showing 27931 to 27940 of 34417 articles

Machine learning-optimized advanced oxidation for enhanced sludge dewatering: EPS mechanistic insights and predictive modeling.

Water research
The recalcitrant nature of extracellular polymeric substances (EPS) in sewage sludge severely limits dewatering efficiency. While advanced oxidation processes (AOPs) disrupt EPS matrices, their optimization remains challenging. This study integrates ...

Evaluating efficacy of 0.125% atropine using a myopia progression machine learning model.

Japanese journal of ophthalmology
PURPOSE: To investigate the usefulness of a machine learning (ML) model that can predict the natural course of childhood myopia in evaluation of the inhibitory effects of 0.125% atropine on the progression of childhood myopia.

Estimation of patient safety culture in private and public hospitals using machine learning methods.

Work (Reading, Mass.)
BackgroundPatient safety is a critical component of health care systems. Large groups of patients, as a result of medical errors, are at risk of harm. OBJECTIVE: This study evaluated the patient safety culture (PSC) between different work groups in b...

Methodological opportunities in genomic data analysis to advance health equity.

Nature reviews. Genetics
The causes and consequences of inequities in genomic research and medicine are complex and widespread. However, it is widely acknowledged that underrepresentation of diverse populations in human genetics research risks exacerbating existing health di...

A Basic Machine Learning Primer for Surgical Research in Congenital Heart Disease.

World journal for pediatric & congenital heart surgery
Artificial intelligence and machine learning are rapidly transforming medicine, healthcare, and surgery. Machine learning is a valuable tool for surgeons and researchers in pediatric cardiovascular and thoracic surgery, with innovative applications c...

Machine-Learning Assisted Screening with FIND FH for Familial Hypercholesterolemia among Youth.

The Journal of pediatrics
Although the American Academy of Pediatrics recommends universal lipid screening among children to find cases of familial hypercholesterolemia, such screening is rarely performed. We report the first clinical use of a novel machine learning model (FI...

Pruning the ensemble of convolutional neural networks using second-order cone programming.

Neural networks : the official journal of the International Neural Network Society
Ensemble techniques are frequently encountered in machine learning and engineering problems since the method combines different models and produces an optimal predictive solution. The ensemble concept can be adapted to deep learning models to provide...

Transcriptome analysis and machine learning methods reveal potential mechanisms of zebrafish muscle aging.

Comparative biochemistry and physiology. Part D, Genomics & proteomics
Muscle is one of the most abundant tissues in the human body, and its aging usually leads to many adverse consequences. Zebrafish is a powerful model used to study human muscle diseases, yet we know little about the molecular mechanisms of muscle agi...

Model-free reinforcement learning control with zero-min barrier functions for constrained systems.

Neural networks : the official journal of the International Neural Network Society
The primary focus of this research is to develop an adaptive output feedback controller designed to minimize a cost-to-go function subject to constraints on input, output, and tracking error for a class of unknown non-affine discrete-time systems. Th...

Learning to solve combinatorial optimization problems with heterophily.

Neural networks : the official journal of the International Neural Network Society
Graph Neural Networks (GNNs) are widely used to address combinatorial optimization problems. However, many popular GNNs struggle to generalize to heterophilic scenarios where adjacent nodes tend to be with different labels or dissimilar features, suc...