AIMC Topic: Uncertainty

Clear Filters Showing 671 to 680 of 706 articles

Beware the Black-Box of Medical Image Generation: an Uncertainty Analysis by the Learned Feature Space.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2022
Deep neural networks (DNNs) are the primary driving force for the current development of medical imaging analysis tools and often provide exciting performance on various tasks. However, such results are usually reported on the overall performance of ...
Diagnostic Imaging Uncertainty Neural Networks, Computer
View on PubMed DOI

Fin-TS and Fix-TS on fractional quaternion delayed neural networks with uncertainty via establishing a new Caputo derivative inequality approach.

Mathematical biosciences and engineering : MBE Jun 23, 2022
This paper investigates the finite time synchronization (Fin-TS) and fixed time synchronization (Fix-TS) issues on Caputo quaternion delayed neural networks (QDNNs) with uncertainty. A new Caputo fractional differential inequality is constructed, the...
Neural Networks, Computer Feedback Time Uncertainty
View on PubMed DOI

A Novel Personalized Random Forest Algorithm for Clinical Outcome Prediction.

Studies in health technology and informatics Jun 6, 2022
Machine learning algorithms that derive predictive models are useful in predicting patient outcomes under uncertainty. These are often "population" algorithms which optimize a static model to predict well on average for individuals in the population;...
Algorithms Prognosis Humans Machine Learning Uncertainty
View on PubMed DOI

Group decision-making analysis with complex spherical fuzzy N-soft sets.

Mathematical biosciences and engineering : MBE Mar 16, 2022
This paper develops the ELiminating Et Choice Translating REality (ELECTRE) method under the generalized environment of complex spherical fuzzy $ N $-soft sets ($ CSFN\mathcal{S}_{f}Ss $) that have distinctive and empirical edge of non-binary paramet...
Algorithms Decision Making Uncertainty Fuzzy Logic
View on PubMed DOI

A new MAGDM method with 2-tuple linguistic bipolar fuzzy Heronian mean operators.

Mathematical biosciences and engineering : MBE Feb 10, 2022
In this article, we introduce the 2-tuple linguistic bipolar fuzzy set (2TLBFS), a new strategy for dealing with uncertainty that incorporates a 2-tuple linguistic term into bipolar fuzzy set. The 2TLBFS is a better way to deal with uncertain and imp...
Research Design Fuzzy Logic Uncertainty Decision Making Linguistics
View on PubMed DOI

On m-polar Diophantine Fuzzy N-soft Set with Applications.

Combinatorial chemistry & high throughput screening Jan 1, 2022
INTRODUCTION: In this paper, we present a novel hybrid model m-polar Diophantine fuzzy N-soft set and define its operations.
Fuzzy Logic Uncertainty
View on PubMed DOI

Comparative analysis of molecular fingerprints in prediction of drug combination effects.

Briefings in bioinformatics Nov 5, 2021
Application of machine and deep learning methods in drug discovery and cancer research has gained a considerable amount of attention in the past years. As the field grows, it becomes crucial to systematically evaluate the performance of novel computa...
High-Throughput Screening Assays Drug Synergism Datasets as Topic Uncertainty Regression Analysis Drug Interactions Computer Simulation Drug Discovery Drug Combinations Deep Learning Humans Cell Line, Tumor
View on PubMed DOI

Deep Learning-Based Segmentation and Uncertainty Assessment for Automated Analysis of Myocardial Perfusion MRI Datasets Using Patch-Level Training and Advanced Data Augmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
In this work, we develop a patch-level training approach and a task-driven intensity-based augmentation method for deep-learning-based segmentation of motion-corrected perfusion cardiac magnetic resonance imaging (MRI) datasets. Further, the proposed...
Uncertainty Heart Perfusion Magnetic Resonance Imaging Deep Learning
View on PubMed DOI

Detecting Uncertainty of Mortality Prediction Using Confident Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Early mortality prediction is an actively researched problem that has led to the development of various severity scores and machine learning (ML) models for accurate and reliable detection of mortality in severely ill patients staying in intensive ca...
Humans Machine Learning Databases, Factual Uncertainty Intensive Care Units Hospital Mortality
View on PubMed DOI

Meeting the unmet needs of clinicians from AI systems showcased for cardiology with deep-learning-based ECG analysis.

Proceedings of the National Academy of Sciences of the United States of America Jun 15, 2021
Despite their great promise, artificial intelligence (AI) systems have yet to become ubiquitous in the daily practice of medicine largely due to several crucial unmet needs of healthcare practitioners. These include lack of explanations in clinically...
Electrocardiography Statistics as Topic Physicians Artificial Intelligence ROC Curve Reproducibility of Results Algorithms Deep Learning Uncertainty Models, Cardiovascular Humans Time Factors Cardiology
View on PubMed DOI
Popular Topics
Recent Journals