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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Methods for Continuous Blood Pressure Estimation Using Temporal Convolutional Neural Networks and Ensemble Empirical Mode Decomposition
Kai Zhou, Zhixiang Yin, Peng Yu, et al.
Electronics (2022) Vol. 11, Iss. 9, pp. 1378-1378
Open Access | Times Cited: 13

Showing 13 citing articles:

Robust optimization for PPG-based blood pressure estimation
Sungjun Lim, Taero Kim, Hyeonjeong Lee, et al.
Biomedical Signal Processing and Control (2025) Vol. 105, pp. 107585-107585
Closed Access
Hyp-Net: Automated detection of hypertension using deep convolutional neural network and Gabor transform techniques with ballistocardiogram signals
Kapil Gupta, Varun Bajaj, Irshad Ahmad Ansari, et al.
Journal of Applied Biomedicine (2022) Vol. 42, Iss. 3, pp. 784-796
Closed Access | Times Cited: 24
A Deep Learning Approach for Generating Intracranial Pressure Waveforms from Extracranial Signals Routinely Measured in the Intensive Care Unit
S Nair, Alina Guo, Joseph Boen, et al.
Computers in Biology and Medicine (2024) Vol. 177, pp. 108677-108677
Closed Access | Times Cited: 4
LGBMDF: A cascade forest framework with LightGBM for predicting drug-target interactions
Yu Peng, Shouwei Zhao, Zhiliang Zeng, et al.
Frontiers in Microbiology (2023) Vol. 13
Open Access | Times Cited: 9
A novel interpretable feature set optimization method in blood pressure estimation using photoplethysmography signals
Jian Liu, Shuaicong Hu, Zhijun Xiao, et al.
Biomedical Signal Processing and Control (2023) Vol. 86, pp. 105184-105184
Closed Access | Times Cited: 8
On the Exploitation of CEEMDAN for PPG Synthetic Data Generation
Alessandra Grossi, Francesca Gasparini, Aurora Saibene
Lecture notes in bioengineering (2024), pp. 56-69
Closed Access | Times Cited: 1
Non-invasive blood pressure estimation combining deep neural networks with pre-training and partial fine-tuning
Ziyan Meng, Xuezhi Yang, Xuenan Liu, et al.
Physiological Measurement (2022) Vol. 43, Iss. 11, pp. 11NT01-11NT01
Closed Access | Times Cited: 6
Real-Time Blood Pressure Prediction Using Apache Spark and Kafka Machine Learning
Ali Farki, Elham Akhondzadeh Noughabi
(2023), pp. 161-166
Closed Access | Times Cited: 3
Photoplethysmography Data Reduction Using Truncated Singular Value Decomposition and Internet of Things Computing
Abdulrahman B. Abdelaziz, Mohammad A. Rahimi, Muhammad Alrabeiah, et al.
Electronics (2023) Vol. 12, Iss. 1, pp. 220-220
Open Access | Times Cited: 2
A Real-Time Deep Learning Approach for Inferring Intracranial Pressure from Routinely Measured Extracranial Waveforms in the Intensive Care Unit
S Nair, Alina Guo, Joseph Boen, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 2
Evaluation of network model for continuous blood pressure without cuffs using photoplethysmography signals
QIN LIU, Jiajian Cao, Yuliang Liu
(2024), pp. 28-28
Closed Access
Integrating Transfer Learning with Scalogram Analysis for Blood Pressure Estimation from PPG Signals
Shyamala Subramanian, Sashikala Mishra, Shruti Patil, et al.
Research Square (Research Square) (2024)
Open Access
An explainable echo state network trained from photoplethysmography signals for equine life stage prediction
Richard Byfield, Morgan Miller, Yunchao Xie, et al.
Neural Computing and Applications (2024) Vol. 36, Iss. 32, pp. 20055-20066
Closed Access
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