AIMC Topic: Algorithms

Clear Filters Showing 3671 to 3680 of 28713 articles

Edge intelligence for poultry welfare: Utilizing tiny machine learning neural network processors for vocalization analysis.

PloS one
The health of poultry flock is crucial in sustainable farming. Recent advances in machine learning and speech analysis have opened up opportunities for real-time monitoring of the behavior and health of flock. However, there has been little research ...

Explainable post hoc portfolio management financial policy of a Deep Reinforcement Learning agent.

PloS one
Financial portfolio management investment policies computed quantitatively by modern portfolio theory techniques like the Markowitz model rely on a set of assumptions that are not supported by data in high volatility markets such as the technological...

Performance of an Algorithm Grading Surgery-Related Adverse Events According to the Clavien-Dindo Classification.

Annals of surgery
OBJECTIVE: To assess the performance of an algorithm for automated grading of surgery-related adverse events (AEs) according to Clavien-Dindo (C-D) classification.

Evaluation of a Deep Learning Denoising Algorithm for Dose Reduction in Whole-Body Photon-Counting CT Imaging: A Cadaveric Study.

Academic radiology
RATIONALE AND OBJECTIVES: Photon Counting CT (PCCT) offers advanced imaging capabilities with potential for substantial radiation dose reduction; however, achieving this without compromising image quality remains a challenge due to increased noise at...

Leveraging neighborhood distance awareness for entity alignment in temporal knowledge graphs.

Neural networks : the official journal of the International Neural Network Society
Entity alignment (EA) is a typical strategy for knowledge graph integration, aiming to identify and align different entity pairs representing the same real object from different knowledge graphs. Temporal Knowledge Graph (TKG) extends the static know...

Severity grading of hypertensive retinopathy using hybrid deep learning architecture.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Hypertensive Retinopathy (HR) is a retinal manifestation resulting from persistently elevated blood pressure. Severity grading of HR is essential for patient risk stratification, effective management, progression monitoring...

UnICLAM: Contrastive representation learning with adversarial masking for unified and interpretable Medical Vision Question Answering.

Medical image analysis
Medical Visual Question Answering aims to assist doctors in decision-making when answering clinical questions regarding radiology images. Nevertheless, current models learn cross-modal representations through residing vision and text encoders in dual...

SIRE: Scale-invariant, rotation-equivariant estimation of artery orientations using graph neural networks.

Medical image analysis
The orientation of a blood vessel as visualized in 3D medical images is an important descriptor of its geometry that can be used for centerline extraction and subsequent segmentation, labeling, and visualization. Blood vessels appear at multiple scal...

Evaluating a clinically available artificial intelligence model for intracranial aneurysm detection: a multi-reader study and algorithmic audit.

Neuroradiology
PURPOSE: We aimed to validate a clinically available artificial intelligence (AI) model to assist general radiologists in the detection of intracranial aneurysm (IA) in a multi-reader multi-case (MRMC) study, and to explore its performance in routine...

Predicting the risk of a high proportion of three/multiple pronuclei (3PN/MPN) zygotes in individual IVF cycles using comparative machine learning algorithms.

European journal of obstetrics, gynecology, and reproductive biology
BACKGROUND: The majority of machine learning applications in assisted reproduction have been focused on predicting the likelihood of pregnancy. In the present study, we aim to investigate which machine learning models are most effective in predicting...