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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:

Developing an AI-assisted clinical decision support system to enhance in-patient holistic health care
Wang‐Chuan Juang, Ming-Hsia Hsu, Zheng-Xun Cai, et al.
PLoS ONE (2022) Vol. 17, Iss. 10, pp. e0276501-e0276501
Open Access | Times Cited: 18

Showing 18 citing articles:

Traditional, complementary, and integrative medicine and artificial intelligence: Novel opportunities in healthcare
Jeremy Y. Ng, Holger Cramer, Myeong Soo Lee, et al.
Integrative Medicine Research (2024) Vol. 13, Iss. 1, pp. 101024-101024
Open Access | Times Cited: 20
Transforming Healthcare with AI: Promises, Pitfalls, and Pathways Forward
Ali Shuaib
International Journal of General Medicine (2024) Vol. Volume 17, pp. 1765-1771
Open Access | Times Cited: 18
The evolving role of nursing informatics in the era of artificial intelligence
Abdulqadir J. Nashwan, JC A. Cabrega, Mutaz I. Othman, et al.
International Nursing Review (2025) Vol. 72, Iss. 1
Open Access | Times Cited: 2
Artificial Intelligence‐Based Medical Sensors for Healthcare System
Mingrui Chen, Daxiang Cui, Hossam Haick, et al.
Advanced Sensor Research (2023) Vol. 3, Iss. 3
Open Access | Times Cited: 26
AI in Indian healthcare: From roadmap to reality
Sushanta Kumar Das, Ramesh Kumari Dasgupta, Saumendu Deb Roy, et al.
Intelligent Pharmacy (2024) Vol. 2, Iss. 3, pp. 329-334
Open Access | Times Cited: 11
Artificial Intelligence in the Diagnosis and Treatment of Pancreatic Cystic Lesions and Adenocarcinoma
Joanna Jiang, Wei‐Lun Chao, Stacey Culp, et al.
Cancers (2023) Vol. 15, Iss. 9, pp. 2410-2410
Open Access | Times Cited: 19
Artificial intelligence and personalized medicine: transforming patient care
Marc Ghanem, Abdul Karim Ghaith, Mohamad Bydon
Elsevier eBooks (2024), pp. 131-142
Closed Access | Times Cited: 6
FastEval Parkinsonism: an instant deep learning–assisted video-based online system for Parkinsonian motor symptom evaluation
Yu-Yuan Yang, Ming-Yang Ho, Chung-Hwei Tai, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 6
The Application of AI in Clinical Nursing, Yields Several Advantageous Outcomes
Habib Ahmed, Naeema Akber, Mohammad Saleem, et al.
Indus journal of bioscience research. (2025) Vol. 3, Iss. 2, pp. 591-599
Closed Access
An LSTM-based decision-making model for predictive manufacturing performance optimization
Hala Mellouli, Anwar Meddaoui, Abdelhamid Zaki, et al.
The International Journal of Advanced Manufacturing Technology (2025)
Closed Access
Volatile organic compounds (VOCs) detection for the identification of bacterial infections in clinical wound samples
Mostafa Azimzadeh, Patricia Khashayar, Marziyeh Mousazadeh, et al.
Talanta (2025) Vol. 292, pp. 127991-127991
Open Access
Unraveling the Black Box: A Review of Explainable Deep Learning Healthcare Techniques
Nafeesa Yousuf Murad, Mohd Hilmi Hasan, Muhammad Hamza Azam, et al.
IEEE Access (2024) Vol. 12, pp. 66556-66568
Open Access | Times Cited: 3
Doctors’ perception on the ethical use of AI-enabled clinical decision support systems for antibiotic prescribing recommendations in Singapore
Zhengying Huang, Hannah Y. Lim, Jing Teng Ow, et al.
Frontiers in Public Health (2024) Vol. 12
Open Access | Times Cited: 2
Developing a deep learning model to predict the breast implant texture types with ultrasonography image: a feasibility study (Preprint)
Ho Heon Kim, Won Chan Jung, Kyungran Pi, et al.
(2024)
Closed Access
Developing a deep learning model to predict the breast implant texture types with ultrasonography image: feasibility study
Ho Heon Kim, Won Chan Jeong, Kyungran Pi, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Developing a deep learning model to predict the breast implant texture types with ultrasonography image: feasibility study (Preprint)
Ho Heon Kim, Won Chan Jeong, Kyungran Pi, et al.
JMIR Formative Research (2024) Vol. 8, pp. e58776-e58776
Open Access
Exploring home healthcare clinicians’ needs for using clinical decision support systems for early risk warning
Zidu Xu, Lauren Evans, Jiyoun Song, et al.
Journal of the American Medical Informatics Association (2024)
Closed Access
Emerging Mobile Health Systems and Services
Theodoros Solomou, Christos N. Schizas, Constantinos S. Pattichis
IntechOpen eBooks (2024)
Open Access
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