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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:

Detecting Congestive Heart Failure by Extracting Multimodal Features and Employing Machine Learning Techniques
Lal Hussain, Imtiaz Ahmed Awan, Wajid Aziz, et al.
BioMed Research International (2020) Vol. 2020, pp. 1-19
Open Access | Times Cited: 75

Showing 1-25 of 75 citing articles:

A Comparative Analysis on the Prediction of Heart Failure using Machine Learning Algorithms
Senthil Pandi S, T Kumaragurubaran, M Jaeyalakshmi, et al.
(2024), pp. 206-211
Closed Access | Times Cited: 25
Classification of normal sinus rhythm, abnormal arrhythmia and congestive heart failure ECG signals using LSTM and hybrid CNN-SVM deep neural networks
Ahmet Çınar, Seda Arslan Tuncer
Computer Methods in Biomechanics & Biomedical Engineering (2020) Vol. 24, Iss. 2, pp. 203-214
Closed Access | Times Cited: 96
Artificial intelligence in the diagnosis and detection of heart failure: the past, present, and future
Farah Yasmin, Syed Muhammad Ismail Shah, Aisha Naeem, et al.
Reviews in Cardiovascular Medicine (2021) Vol. 22, Iss. 4
Open Access | Times Cited: 91
Coronary artery disease detection using artificial intelligence techniques: A survey of trends, geographical differences and diagnostic features 1991–2020
Roohallah Alizadehsani, Abbas Khosravi, Mohamad Roshanzamir, et al.
Computers in Biology and Medicine (2020) Vol. 128, pp. 104095-104095
Closed Access | Times Cited: 90
Heart rate variability and obstructive sleep apnea: Current perspectives and novel technologies
Seren Ucak, Hasthi U. Dissanayake, Kate Sutherland, et al.
Journal of Sleep Research (2021) Vol. 30, Iss. 4
Closed Access | Times Cited: 75
Machine Learning-Based Automated Diagnostic Systems Developed for Heart Failure Prediction Using Different Types of Data Modalities: A Systematic Review and Future Directions
Ashir Javeed, Shafqat Ullah Khan, Liaqat Ali, et al.
Computational and Mathematical Methods in Medicine (2022) Vol. 2022, pp. 1-30
Open Access | Times Cited: 62
Artificial intelligence and heart failure: A state‐of‐the‐art review
Muhammad Shahzeb Khan, Muhammad Sameer Arshad, Stephen J. Greene, et al.
European Journal of Heart Failure (2023) Vol. 25, Iss. 9, pp. 1507-1525
Closed Access | Times Cited: 29
Artificial Intelligence in Heart Failure: Friend or Foe?
Angeliki Bourazana, Αndrew Xanthopoulos, Αlexandros Briasoulis, et al.
Life (2024) Vol. 14, Iss. 1, pp. 145-145
Open Access | Times Cited: 12
Artificial Intelligence based accurately load forecasting system to forecast short and medium-term load demands
Faisal Mehmood Butt, Lal Hussain, Anzar Mahmood, et al.
Mathematical Biosciences & Engineering (2020) Vol. 18, Iss. 1, pp. 400-425
Open Access | Times Cited: 50
Time adaptive ECG driven cardiovascular disease detector
Muhammad Salman Haleem, Rossana Castaldo, Silvio Marcello Pagliara, et al.
Biomedical Signal Processing and Control (2021) Vol. 70, pp. 102968-102968
Open Access | Times Cited: 47
A Machine Learning Approach for Chronic Heart Failure Diagnosis
Dafni K. Plati, Evanthia E. Tripoliti, Aris Bechlioulis, et al.
Diagnostics (2021) Vol. 11, Iss. 10, pp. 1863-1863
Open Access | Times Cited: 41
The Deep Learning ResNet101 and Ensemble XGBoost Algorithm with Hyperparameters Optimization Accurately Predict the Lung Cancer
Saghir Ahmed, Basit Raza, Lal Hussain, et al.
Applied Artificial Intelligence (2023) Vol. 37, Iss. 1
Open Access | Times Cited: 18
Ambient assisted living predictive model for cardiovascular disease prediction using supervised learning
Sibo Prasad Patro, Neelamadhab Padhy, Dukuru Chiranjevi
Evolutionary Intelligence (2020) Vol. 14, Iss. 2, pp. 941-969
Closed Access | Times Cited: 42
Detecting brain tumors using deep learning convolutional neural network with transfer learning approach
Sadia Anjum, Lal Hussain, Mushtaq Ali, et al.
International Journal of Imaging Systems and Technology (2021) Vol. 32, Iss. 1, pp. 307-323
Closed Access | Times Cited: 39
Temporal Feature-Based Classification Into Myocardial Infarction and Other CVDs Merging CNN and Bi-LSTM From ECG Signal
Monisha Dey, Nuzaer Omar, Muhammad Ahsan Ullah
IEEE Sensors Journal (2021) Vol. 21, Iss. 19, pp. 21688-21695
Closed Access | Times Cited: 35
Imbalanced ECG signal-based heart disease classification using ensemble machine learning technique
Adyasha Rath, Debahuti Mishra, Ganapati Panda
Frontiers in Big Data (2022) Vol. 5
Open Access | Times Cited: 22
Circadian assessment of heart failure using explainable deep learning and novel multi-parameter polar images
Mohanad Alkhodari, Ahsan H. Khandoker, Herbert F. Jelinek, et al.
Computer Methods and Programs in Biomedicine (2024) Vol. 248, pp. 108107-108107
Open Access | Times Cited: 4
Heart failure survival prediction using novel transfer learning based probabilistic features
Azam Mehmood Qadri, Muhammad Shadab Alam Hashmi, Ali Raza, et al.
PeerJ Computer Science (2024) Vol. 10, pp. e1894-e1894
Open Access | Times Cited: 4
Revolutionizing Cardiac Care: Artificial Intelligence Applications in Heart Failure Management
Areeba Fareed, Rayyan Vaid, Abdulrahmon Moradeyo, et al.
Cardiology in Review (2025)
Closed Access
Efficacy of AI Models in Detecting Heart Failure Using ECG Data: A Systematic Review and Meta-Analysis
Salman Khan, Komal Qayyum, A QADEER, et al.
Cureus (2025)
Open Access
Optimizing Classification of Congestive Heart Failure Using Feature Weight Importance Correlation
Iyabosola Busola Oronti, Muhammad Salman Haleem, Leandro Pecchia, et al.
Communications in computer and information science (2025), pp. 24-31
Closed Access
Optimizing Bi-LSTM networks for improved lung cancer detection accuracy
Su Diao, Yajie Wan, Danyi Huang, et al.
PLoS ONE (2025) Vol. 20, Iss. 2, pp. e0316136-e0316136
Open Access
Time-Adaptive Machine Learning Models for Predicting the Severity of Heart Failure with Reduced Ejection Fraction
Trevor Winger, Cagri Ozdemir, Shanti L. Narasimhan, et al.
Diagnostics (2025) Vol. 15, Iss. 6, pp. 715-715
Open Access
Harnessing Electronic Health Records and Artificial Intelligence for Enhanced Cardiovascular Risk Prediction: A Comprehensive Review
Ming‐Lung Tsai, Kuan‐Fu Chen, Pei‐Chun Chen
Journal of the American Heart Association (2025)
Open Access
Machine learning based congestive heart failure detection using feature importance ranking of multimodal features
Lal Hussain, Wajid Aziz, Ishtiaq Rasool Khan, et al.
Mathematical Biosciences & Engineering (2020) Vol. 18, Iss. 1, pp. 69-91
Open Access | Times Cited: 34
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