AIMC Topic: Algorithms

Clear Filters Showing 23811 to 23820 of 28713 articles

A Survey of Deep Learning in Sports Applications: Perception, Comprehension, and Decision.

IEEE transactions on visualization and computer graphics
Deep learning has the potential to revolutionize sports performance, with applications ranging from perception and comprehension to decision. This article presents a comprehensive survey of deep learning in sports performance, focusing on three main ...

Real-Time Imaging Enhancement of Handheld Photoacoustic System With FeRAM Crossbar Array Based Neuromorphic Design.

IEEE transactions on biomedical circuits and systems
The miniaturization and real time imaging capability have always been the desired properties of photoacoustic imaging (PAI) system, which unlocked vast potential for personalized healthcare and diagnostics. While the imaging quality and resolution in...

Machine learning algorithms with body fluid parameters: an interpretable framework for malignant cell screening in cerebrospinal fluid.

Clinical chemistry and laboratory medicine
OBJECTIVES: This study aimed to develop and validate a machine learning (ML) model utilizing cerebrospinal fluid (CSF) body fluid parameters from hematology analyzers to screen for malignant cells.

Can polycythaemia vera disease be predicted from haematologic parameters? A machine learning-based study.

Journal of clinical pathology
AIMS: The aim of this research is to diagnose polycythaemia vera (PV) disease using different machine learning (ML) algorithms with complete blood count (CBC) parameters before further investigations such as Janus kinase 2 (), erythropoietin (EPO) an...

Machine learning classification of quorum sensing-induced bacterial aggregation using flow rate assays on paper chips toward bacterial species identification in potable water sources.

Biosensors & bioelectronics
Preventing waterborne disease caused by bacteria is especially important in low-resource settings, where skilled personnel and laboratory equipment are scarce. This work reports a straightforward method for classifying bacterial species by monitoring...

Incorporating respiratory signals for machine learning-based multimodal sleep stage classification: a large-scale benchmark study with actigraphy and heart rate variability.

Sleep
Insufficient sleep quality is directly linked to various diseases, making reliable sleep monitoring crucial for prevention, diagnosis, and treatment. As sleep laboratories are cost- and resource-prohibitive, wearable sensors offer a promising alterna...

Energy entropy vector: a novel approach for efficient microbial genomic sequence analysis and classification.

Briefings in bioinformatics
With the rapid development of genomic sequencing technologies, there is an increasing demand for efficient and accurate sequence analysis methods. However, existing methods face challenges in handling long, variable-length sequences and large-scale d...

Compositional analysis of alternative protein blends using near and mid-infrared spectroscopy coupled with conventional and machine learning algorithms.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The non-invasive real-time analysis of the composition of alternative, plant-based protein sources is important to control high moisture extrusion processes and ensure the quality and texture of the final extrudates used in the elaboration of meat an...

Towards Fairness in Synthetic Healthcare Data: A Framework for the Evaluation of Synthetization Algorithms.

Studies in health technology and informatics
INTRODUCTION: Synthetic data generation is a rapidly evolving field, with significant potential for improving data privacy. However, evaluating the performance of synthetic data generation methods, especially the tradeoff between fairness and utility...

Ensemble of Bayesian alphabets via constraint weight optimization strategy improves genomic prediction accuracy.

G3 (Bethesda, Md.)
This study proposes a weight optimization-based ensemble framework aimed at improving genomic prediction accuracy. It incorporates 8 Bayesian models-BayesA, BayesB, BayesC, BayesBpi, BayesCpi, BayesR, BayesL, and BayesRR in the ensemble framework, wh...