AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Bayes Theorem

Showing 101 to 110 of 1710 articles

Clear Filters

Uncertainty-aware diabetic retinopathy detection using deep learning enhanced by Bayesian approaches.

Scientific reports
Deep learning-based medical image analysis has shown strong potential in disease categorization, segmentation, detection, and even prediction. However, in high-stakes and complex domains like healthcare, the opaque nature of these models makes it cha...

SRADHO: statistical reduction approach with deep hyper optimization for disease classification using artificial intelligence.

Scientific reports
Artificial Intelligence techniques are being used to analyse vast amounts of medical data and assist in the accurate and early diagnosis of diseases. The common brain related diseases are faced by most of the people which affects the structure and fu...

Intelligence analysis of drug nanoparticles delivery efficiency to cancer tumor sites using machine learning models.

Scientific reports
This study focuses on the use of machine learning (ML) models to predict the biodistribution of nanoparticles in various organs, using a dataset derived from research on nanoparticle behavior for cancer treatment. The dataset includes both categorica...

A novel RFE-GRU model for diabetes classification using PIMA Indian dataset.

Scientific reports
Diabetes is a long-term condition characterized by elevated blood sugar levels. It can lead to a variety of complex disorders such as stroke, renal failure, and heart attack. Diabetes requires the most machine learning help to diagnose diabetes illne...

Spatiotemporal multi-feature fusion vehicle trajectory anomaly detection for intelligent transportation: An improved method combining autoencoders and dynamic Bayesian networks.

Accident; analysis and prevention
With the continuous development of intelligent transportation systems, traffic safety has become a major societal concern, and vehicle trajectory anomaly detection technology has emerged as a crucial method to ensure safety. However, current technolo...

Explainable artificial intelligence with UNet based segmentation and Bayesian machine learning for classification of brain tumors using MRI images.

Scientific reports
Detecting brain tumours (BT) early improves treatment possibilities and increases patient survival rates. Magnetic resonance imaging (MRI) scanning offers more comprehensive information, such as better contrast and clarity, than any alternative scann...

A Systematic Approach to Prioritise Diagnostically Useful Findings for Inclusion in Electronic Health Records as Discrete Data to Improve Clinical Artificial Intelligence Tools and Genomic Research.

Clinical oncology (Royal College of Radiologists (Great Britain))
AIMS: The recent widespread use of electronic health records (EHRs) has opened the possibility for innumerable artificial intelligence (AI) tools to aid in genomics, phenomics, and other research, as well as disease prevention, diagnosis, and therapy...

A new prediction model based on deep learning for pig house environment.

Scientific reports
A prediction model of the pig house environment based on Bayesian optimization (BO), squeeze and excitation block (SE), convolutional neural network (CNN) and gated recurrent unit (GRU) is proposed to improve the prediction accuracy and animal welfar...

Comparison of population pharmacokinetic modeling and machine learning approaches for predicting voriconazole trough concentrations in critically ill patients.

International journal of antimicrobial agents
BACKGROUND: Despite the widespread use of voriconazole in antifungal treatment, its high pharmacokinetic and pharmacodynamic variability may lead to suboptimal efficacy, especially in intensive care unit (ICU) patients. Machine learning (ML), an arti...

Machine learning mathematical models for incidence estimation during pandemics.

PLoS computational biology
Accurate estimates of the incidence of infectious diseases are key for the control of epidemics. However, healthcare systems are often unable to test the population exhaustively, especially when asymptomatic and paucisymptomatic cases are widespread;...