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Machine learning and blood pressure

Published:2019-09-19 Issue:11 Volume:21 Page:1735-1737
ISSN:1524-6175
Container-title:The Journal of Clinical Hypertension
language:en
Short-container-title:J Clin Hypertens

Author:

Santhanam Prasanna¹^ORCID,Ahima Rexford S.¹

Affiliation:

1. Division of Endocrinology Diabetes, & Metabolism Department of Medicine Johns Hopkins University School of Medicine Baltimore MD USA

Publisher

Wiley

Subject

Cardiology and Cardiovascular Medicine,Endocrinology, Diabetes and Metabolism,Internal Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jch.13700

Reference15 articles.

1. M BC. Pattern Recognition and Machine Learning.SPRINGER.2006(ISBN 978‐0‐387‐31073‐2).

2. Machine learning.https://en.wikipedia.org/wiki/Machine_learning#Feature_learning

3. Modelling the relationship between peripheral blood pressure and blood volume pulses using linear and neural network system identification techniques

4. Risk factors for coronary artery disease and the use of neural networks to predict the presence or absence of high blood pressure

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2. Exploring the diagnostic performance of machine learning in prediction of metabolic phenotypes focusing on thyroid function;PLOS ONE;2024-06-28

3. Hypotension prediction index for the prevention of hypotension during surgery and critical care: A narrative review;Computers in Biology and Medicine;2024-03

4. A comprehensive evaluation of ensemble learning methods and decision trees for predicting trauma patient discharge status using real-world data;ARCH TRAUMA RES;2023

5. Improving PPG Signal Classification with Machine Learning: The Power of a Second Opinion;2023 24th International Conference on Digital Signal Processing (DSP);2023-06-11

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