Noninvasive Blood Pressure Classification Based on Photoplethysmography Using K-Nearest Neighbors Algorithm: A Feasibility Study

Information (Switzerland) - Switzerland
doi 10.3390/info11020093
Full Text
Abstract

Available in full text

Date
Authors

Unknown

Publisher

MDPI AG

Related search

Predicting Software Faults Based on K-Nearest Neighbors Classification

International Journal of Computing and Digital Systems
Computer GraphicsHuman-Computer InteractionComputer NetworksCommunicationsInformation SystemsComputer-Aided DesignInnovationManagement of TechnologyArtificial Intelligence
2019English

Performance of K-Nearest Neighbors Algorithm in Opinion Classification

Foundations of Computing and Decision Sciences
Computer ScienceTheoretical Computer Science
2013English

A Weighted Similarity Measure for K-Nearest Neighbors Algorithm

Celal Bayar Üniversitesi Fen Bilimleri Dergisi
2019English

RGBD Human Action Recognition Using Multi-Features Combination and K-Nearest Neighbors Classification

International Journal of Advanced Computer Science and Applications
Computer Science
2017English

A Randomized Approximate Nearest Neighbors Algorithm

Applied and Computational Harmonic Analysis
Applied Mathematics
2013English

Randomized Approximate Nearest Neighbors Algorithm

Proceedings of the National Academy of Sciences of the United States of America
Multidisciplinary
2011English

LQ45 Stock Index Prediction Using K-Nearest Neighbors Regression

International Journal of Recent Technology and Engineering
EngineeringManagement of TechnologyInnovation
2019English

Evaluation of Noninvasive Blood Pressure Recording by Photoplethysmography in Clinical Studies Using Angiotensin Challenges

British Journal of Clinical Pharmacology
Pharmacology
2001English

Introduction to Machine Learning: K-Nearest Neighbors

Annals of Translational Medicine
Medicine
2016English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy