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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:

Designing interpretable ML system to enhance trust in healthcare: A systematic review to proposed responsible clinician-AI-collaboration framework
Elham Nasarian, Roohallah Alizadehsani, U. Rajendra Acharya, et al.
Information Fusion (2024) Vol. 108, pp. 102412-102412
Open Access | Times Cited: 25

Showing 25 citing articles:

A review of Explainable Artificial Intelligence in healthcare
Zahra Sadeghi, Roohallah Alizadehsani, Mehmet Akif Çifçi, et al.
Computers & Electrical Engineering (2024) Vol. 118, pp. 109370-109370
Open Access | Times Cited: 41
Artificial Intelligence and Neuroscience: Transformative Synergies in Brain Research and Clinical Applications
Răzvan Onciul, Cătălina-Ioana Tătaru, Adrian Dumitru, et al.
Journal of Clinical Medicine (2025) Vol. 14, Iss. 2, pp. 550-550
Open Access | Times Cited: 3
An Interpretable and Generalizable Machine Learning Model for Predicting Asthma Outcomes: Integrating AutoML and Explainable AI Techniques
Salman Mahmood, Raza Hasan, Saqib Hussain, et al.
World (2025) Vol. 6, Iss. 1, pp. 15-15
Open Access | Times Cited: 1
Large Language Models in Biomedical and Health Informatics: A Review with Bibliometric Analysis
Huizi Yu, Lizhou Fan, Lingyao Li, et al.
Journal of Healthcare Informatics Research (2024) Vol. 8, Iss. 4, pp. 658-711
Closed Access | Times Cited: 5
Transforming Cardiovascular Risk Prediction: A Review of Machine Learning and Artificial Intelligence Innovations
Dimitrios-Ioannis Kasartzian, Thomas Tsiampalis
Life (2025) Vol. 15, Iss. 1, pp. 94-94
Open Access
An explainable transformer model integrating PET and tabular data for histologic grading and prognosis of follicular lymphoma: a multi-institutional digital biopsy study
Chong Jiang, Zekun Jiang, Zitong Zhang, et al.
European Journal of Nuclear Medicine and Molecular Imaging (2025)
Closed Access
MS-RRBR: A Multi-Model Synergetic Framework for Restricted and Repetitive Behavior Recognition in Children with Autism
Yonggu Wang, Yujun Shao, Zengyi Yu, et al.
Applied Sciences (2025) Vol. 15, Iss. 3, pp. 1577-1577
Open Access
Dynamic Surgical Prioritization: A Machine Learning and XAI-Based Strategy
Fabián Silva-Aravena, Jenny Morales, Manoj Jayabalan, et al.
Technologies (2025) Vol. 13, Iss. 2, pp. 72-72
Open Access
Machine Learning-Driven Predictive Modeling for Lipid Oxidation Stability in Emulsions: A Smart Food Safety Strategy
Lijun Liu, Yang Li, Mengjie Zhu, et al.
Trends in Food Science & Technology (2025), pp. 104972-104972
Closed Access
From classical approaches to artificial intelligence, old and new tools for PDAC risk stratification and prediction
Riccardo Farinella, Alessio Felici, Giulia Peduzzi, et al.
Seminars in Cancer Biology (2025)
Open Access
Interpretable Lung Cancer Risk Prediction Using Ensemble Learning and XAI Based on Lifestyle and Demographic Data
Shahid Mohammad Ganie, Pijush Kanti Dutta Pramanik
Computational Biology and Chemistry (2025), pp. 108438-108438
Closed Access
Hybrid weighted fuzzy production rule extraction utilizing modified harmony search and BPNN
Feng Qin, Azlan Mohd Zain, Kai-qing ZHOU, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Machine learning in point-of-care testing: innovations, challenges, and opportunities
Gyeo‐Re Han, Artem Goncharov, Merve Eryılmaz, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access
Interpretation of Artificial Intelligence Models in Healthcare
Ali Abbasian Ardakani, Omid Airom, Hamid Khorshidi, et al.
Journal of Ultrasound in Medicine (2024) Vol. 43, Iss. 10, pp. 1789-1818
Closed Access | Times Cited: 3
Machine Learning-Based Process Optimization in Biopolymer Manufacturing: A Review
Ivan Malashin, D. A. Martysyuk, В С Тынченко, et al.
Polymers (2024) Vol. 16, Iss. 23, pp. 3368-3368
Open Access | Times Cited: 3
Cultivating diagnostic clarity: The importance of reporting artificial intelligence confidence levels in radiologic diagnoses
Mobina Fathi, Kimia Vakili, Ramtin Hajibeygi, et al.
Clinical Imaging (2024) Vol. 117, pp. 110356-110356
Closed Access | Times Cited: 1
MLHOps: Machine Learning Health Operations
Faiza Khan Khattak, Vallijah Subasri, Amrit Krishnan, et al.
IEEE Access (2024) Vol. 13, pp. 20374-20412
Open Access | Times Cited: 1
The Cognitive, Age, Functioning, and Apolipoprotein E4 (CAFE) Scorecard to Predict the Development of Alzheimer’s Disease: A White-Box Approach
Yumiko Wiranto, Devin R Setiawan, Amber Watts, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Analysis of Artificial Intelligence Methods in Classifying Heart Attack Risk: Black-Box Models vs. Glass-Box Models
Ebru Geçici, Eyüp Ensar Işık, Mısra Şimşir, et al.
International Journal of Advances in Engineering and Pure Sciences (2024)
Closed Access
Bridging Human and Machine Intelligence: Reverse-Engineering Radiologist Intentions for Clinical Trust and Adoption
Akash Awasthi, Ngan Le, Zhigang Deng, et al.
Computational and Structural Biotechnology Journal (2024) Vol. 24, pp. 711-723
Open Access
A Framework for a Master’s in Applied Artificial Intelligence Program in Computer and Information Systems Discipline
Abdur R. Shahid, Sushma Mishra
Deleted Journal (2024) Vol. 35, Iss. 4, pp. 495-511
Closed Access
Sleep apnea events recognition based on polysomnographic recordings: a large-scale multi-channel machine learning approach
Nicolò La Porta, Stefano Scafa, Michela Papandrea, et al.
IEEE Open Journal of Engineering in Medicine and Biology (2024) Vol. 6, pp. 202-211
Open Access
Trust in AI-Based Clinical Decision Support Systems Among Healthcare Workers: A Systematic Review (Preprint)
Hein Minn Tun, Hanif Abdul Rahman, Lin Naing, et al.
(2024)
Open Access
A Comprehensive Framework for Transparent and Explainable AI Sensors in Healthcare
Rabaï Bouderhem
(2024), pp. 49-49
Open Access
Trust in AI-Based Clinical Decision Support Systems Among Healthcare Workers: A Systematic Review (Preprint)
Hein Minn Tun, Hanif Abdul Rahman, Lin Naing, et al.
Journal of Medical Internet Research (2024)
Open Access
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