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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:

Classification of blood pressure in critically ill patients using photoplethysmography and machine learning
Elisa Mejía‐Mejía, James M. May, Mohamed Elgendi, et al.
Computer Methods and Programs in Biomedicine (2021) Vol. 208, pp. 106222-106222
Closed Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

Application of photoplethysmography signals for healthcare systems: An in-depth review
Hui Wen Loh, Shuting Xu, Oliver Faust, et al.
Computer Methods and Programs in Biomedicine (2022) Vol. 216, pp. 106677-106677
Open Access | Times Cited: 71
Intelligent Wearable Systems: Opportunities and Challenges in Health and Sports
Luyao Yang, Osama Amin, Basem Shihada
ACM Computing Surveys (2024) Vol. 56, Iss. 7, pp. 1-42
Closed Access | Times Cited: 21
MLP-BP: A novel framework for cuffless blood pressure measurement with PPG and ECG signals based on MLP-Mixer neural networks
Bin Huang, Weihai Chen, Chun‐Liang Lin, et al.
Biomedical Signal Processing and Control (2021) Vol. 73, pp. 103404-103404
Closed Access | Times Cited: 62
ExHyptNet: An explainable diagnosis of hypertension using EfficientNet with PPG signals
El‐Sayed A. El‐Dahshan, Mahmoud M. Bassiouni, Smith K. Khare, et al.
Expert Systems with Applications (2023) Vol. 239, pp. 122388-122388
Closed Access | Times Cited: 24
A Deep Learning Approach for Atrial Fibrillation Classification Using Multi-Feature Time Series Data from ECG and PPG
Bader Aldughayfiq, Farzeen Ashfaq, N. Z. Jhanjhi, et al.
Diagnostics (2023) Vol. 13, Iss. 14, pp. 2442-2442
Open Access | Times Cited: 22
Recent Advances in Non-Invasive Blood Pressure Monitoring and Prediction Using a Machine Learning Approach
Siti Nor Ashikin Ismail, Nazrul Anuar Nayan, Rosmina Jaafar, et al.
Sensors (2022) Vol. 22, Iss. 16, pp. 6195-6195
Open Access | Times Cited: 28
Survey and Evaluation of Hypertension Machine Learning Research
Clea du Toit, Tran Tran, Neha Deo, et al.
Journal of the American Heart Association (2023) Vol. 12, Iss. 9
Open Access | Times Cited: 13
Comparison of pulse rate variability and morphological features of photoplethysmograms in estimation of blood pressure
Elisa Mejía‐Mejía, Karthik Budidha, P. A. Kyriacou, et al.
Biomedical Signal Processing and Control (2022) Vol. 78, pp. 103968-103968
Open Access | Times Cited: 14
Nonlinear features of photoplethysmography signals for Non-invasive blood pressure estimation
Fatemeh Shoeibi, Esmaeil Najafiaghdam, Afshin Ebrahimi
Biomedical Signal Processing and Control (2023) Vol. 85, pp. 105067-105067
Closed Access | Times Cited: 8
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
A novel CS-NET architecture based on the unification of CNN, SVM and super-resolution spectrogram to monitor and classify blood pressure using photoplethysmography
Pankaj, Ashish Kumar, Rama Komaragiri, et al.
Computer Methods and Programs in Biomedicine (2023) Vol. 240, pp. 107716-107716
Closed Access | Times Cited: 8
Automatic identification of hypertension and assessment of its secondary effects using artificial intelligence: A systematic review (2013–2023)
Anjan Gudigar, Nahrizul Adib Kadri, U. Raghavendra, et al.
Computers in Biology and Medicine (2024) Vol. 172, pp. 108207-108207
Open Access | Times Cited: 2
A Data-Driven Model with Feedback Calibration Embedded Blood Pressure Estimator Using Reflective Photoplethysmography
Jiawei Chen, Hsin-Kai Huang, Yu-Ting Fang, et al.
Sensors (2022) Vol. 22, Iss. 5, pp. 1873-1873
Open Access | Times Cited: 11
Cuffless blood pressure estimation using chaotic features of photoplethysmograms and parallel convolutional neural network
Mohammad Bagher Khodabakhshi, Naeem Eslamyeh, Seyede Zohreh Sadredini, et al.
Computer Methods and Programs in Biomedicine (2022) Vol. 226, pp. 107131-107131
Closed Access | Times Cited: 11
Analysis of photoplethysmogram signal to estimate heart rate during physical activity using fractional fourier transform – A sampling frequency independent and reference signal-less method
Pankaj, Ashish Kumar, Aryaman Ashdhir, et al.
Computer Methods and Programs in Biomedicine (2022) Vol. 229, pp. 107294-107294
Closed Access | Times Cited: 11
Development of continuous cuffless blood pressure prediction platform using enhanced 1-D SENet–LSTM
Gengjia Zhang, Daegil Choi, Jaehyo Jung
Expert Systems with Applications (2023) Vol. 242, pp. 122812-122812
Closed Access | Times Cited: 6
Real-Time Cuffless Continuous Blood Pressure Estimation Using 1D Squeeze U-Net Model: A Progress toward mHealth
Tasbiraha Athaya, Sunwoong Choi
Biosensors (2022) Vol. 12, Iss. 8, pp. 655-655
Open Access | Times Cited: 9
Classification of pulmonary arterial pressure using photoplethysmography and bi-directional LSTM
Qian Zhang, Pei Ma
Biomedical Signal Processing and Control (2023) Vol. 86, pp. 105071-105071
Closed Access | Times Cited: 5
Regression or Classification? Reflection on BP prediction from PPG data using Deep Neural Networks in the scope of practical applications
Fabian Schrumpf, Paul Rudi Serdack, Mirco Fuchs
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (2022), pp. 2171-2180
Open Access | Times Cited: 8
Prediction of arterial blood pressure waveforms based on Multi-Task learning
Gang Ma, Lesong Zheng, Wenliang Zhu, et al.
Biomedical Signal Processing and Control (2024) Vol. 92, pp. 106070-106070
Closed Access | Times Cited: 1
A Deep Learning Approach for Non-Invasive Hypertension Classification from PPG Signal
Rifah Tasnim Haque Promi, Rezwana Akter Nazri, Md. Shahidul Salim, et al.
(2023) Vol. 73, pp. 1-5
Closed Access | Times Cited: 2
Detecção de Hipertensão Arterial usando Fotopletismografia e Aprendizado de Máquina
Douglas Henz, André Luís Del Mestre Martins, Juliano Costa Machado, et al.
(2024), pp. 110-117
Open Access
Robust arterial compliance estimation with Katz’s fractal dimension of photoplethysmography
Xiaoman Xing, Jingyuan Hong, Jordi Alastruey, et al.
Frontiers in Physiology (2024) Vol. 15
Open Access
Towards Finger Pulse Photoplethysmogram Based Non-invasive Classification of Diabetic versus Normal
Shikha Agarwal, Rakesh Kumar Sinha
Lecture notes in networks and systems (2024), pp. 115-135
Closed Access
Improved Hypertension Detection Models Utilizing Pulse Rate Variability and Asymmetry
Aikaterini Vraka, Lorenzo Fácila, Fernando Hornero, et al.
IFMBE proceedings (2024), pp. 162-170
Closed Access
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