AIMC Topic: Artificial Intelligence

Clear Filters Showing 14171 to 14180 of 26332 articles

On evaluation metrics for medical applications of artificial intelligence.

Scientific reports
Clinicians and software developers need to understand how proposed machine learning (ML) models could improve patient care. No single metric captures all the desirable properties of a model, which is why several metrics are typically reported to summ...

Artificial intelligence and machine learning in precision medicine: A paradigm shift in big data analysis.

Progress in molecular biology and translational science
The integration of artificial intelligence in precision medicine has revolutionized healthcare delivery. Precision medicine identifies the phenotype of particular patients with less-common responses to treatment. Recent studies have demonstrated that...

Facilitating the Work of Unmanned Aerial Vehicle Operators Using Artificial Intelligence: An Intelligent Filter for Command-and-Control Maps to Reduce Cognitive Workload.

Human factors
OBJECTIVE: Evaluating the ability of a Gibsonian-inspired artificial intelligence (AI) algorithm to reduce the cognitive workloads of military Unmanned Aerial Vehicle (UAV) operators.

Engaging children and young people on the potential role of artificial intelligence in medicine.

Pediatric research
INTRODUCTION: There is increasing interest in Artificial Intelligence (AI) and its application to medicine. Perceptions of AI are less well-known, notably amongst children and young people (CYP). This workshop investigates attitudes towards AI and it...

A cost-aware framework for the development of AI models for healthcare applications.

Nature biomedical engineering
Accurate artificial intelligence (AI) for disease diagnosis could lower healthcare workloads. However, when time or financial resources for gathering input data are limited, as in emergency and critical-care medicine, developing accurate AI models, w...

Development of a Visualization Deep Learning Model for Classifying Origins of Ventricular Arrhythmias.

Circulation journal : official journal of the Japanese Circulation Society
BACKGROUND: Several algorithms have been proposed for differentiating the right and left outflow tracts (RVOT/LVOT) arrhythmia origins from 12-lead electrocardiograms (ECGs); however, the procedure is complicated. A deep learning (DL) model, a form o...

Artificial intelligence: a solution to involution of design-build-test-learn cycle.

Current opinion in biotechnology
Iterative design-build-test-learn (DBTL) cycles are routinely performed during microbial strain development. This useful approach integrates computational strain design, genetic engineering, fermentation testing, and omics analysis to reveal and reso...

Fundamental and practical aspects of machine learning for the peak picking of biomolecular NMR spectra.

Journal of biomolecular NMR
Rapid progress in machine learning offers new opportunities for the automated analysis of multidimensional NMR spectra ranging from protein NMR to metabolomics applications. Most recently, it has been demonstrated how deep neural networks (DNN) desig...

Dynamic QoS Management for a Flexible 5G/6G Network Core: A Step toward a Higher Programmability.

Sensors (Basel, Switzerland)
The academic and professional community has recently started to develop the concept of 6G networks. The scientists have defined key performance indicators and pursued large-scale automation, ambient sensing intelligence, and pervasive artificial inte...

Training and clinical testing of artificial intelligence derived right atrial cardiovascular magnetic resonance measurements.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Right atrial (RA) area predicts mortality in patients with pulmonary hypertension, and is recommended by the European Society of Cardiology/European Respiratory Society pulmonary hypertension guidelines. The advent of deep learning may al...