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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 models for assessing coronary artery disease instances using clinical and biometric data: an explainable man-in-the-loop approach
Agorastos-Dimitrios Samaras, Serafeim Moustakidis, Ioannis D. Apostolopoulos, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 10

Showing 10 citing articles:

Advancements and applications of Artificial Intelligence in cardiology: Current trends and future prospects
David B. Olawade, Nicholas Aderinto, Gbolahan Olatunji, et al.
Journal of Medicine Surgery and Public Health (2024) Vol. 3, pp. 100109-100109
Open Access | Times Cited: 7
Explainable Deep Fuzzy Cognitive Map Diagnosis of Coronary Artery Disease: Integrating Myocardial Perfusion Imaging, Clinical Data, and Natural Language Insights
Anna Feleki, Ioannis D. Apostolopoulos, Serafeim Moustakidis, et al.
Applied Sciences (2023) Vol. 13, Iss. 21, pp. 11953-11953
Open Access | Times Cited: 9
Application of Machine Learning in Healthcare and Medicine: A Review
Furizal Furizal, Alfian Ma’arif, Dianda Rifaldi
Journal of Robotics and Control (JRC) (2023) Vol. 4, Iss. 5, pp. 621-631
Open Access | Times Cited: 6
Integrating Machine Learning in Clinical Practice for Characterizing the Malignancy of Solitary Pulmonary Nodules in PET/CT Screening
Ioannis D. Apostolopoulos, Νικόλαος Παπαθανασίου, D. Apostolopoulos, et al.
Diseases (2024) Vol. 12, Iss. 6, pp. 115-115
Open Access | Times Cited: 1
Uncovering the Black Box of Coronary Artery Disease Diagnosis: The Significance of Explainability in Predictive Models
Agorastos-Dimitrios Samaras, Serafeim Moustakidis, Ioannis D. Apostolopoulos, et al.
Applied Sciences (2023) Vol. 13, Iss. 14, pp. 8120-8120
Open Access | Times Cited: 2
Consistency, local stability, and approximation of Shapash explanation
Tsehay Admassu Assegie, Bommy Manivannan, N. Komal Kumar, et al.
TELKOMNIKA (Telecommunication Computing Electronics and Control) (2024) Vol. 22, Iss. 3, pp. 673-673
Open Access
Explainable Yolov8 Model for Solitary Pulmonary Nodules Classification Using Positron Emission Tomography and Computed Tomography Scans
Agorastos-Dimitrios Samaras, Ioannis D. Apostolopoulos, Elpiniki I. Papageorgiou, et al.
(2024)
Closed Access
A Review on Heart Diseases Using Machine Learning and Deep Learning Techniques
K Mallikarjunamallu, Khasim Syed
Lecture notes in networks and systems (2024), pp. 651-679
Closed Access
A Multi-Modal Machine Learning Methodology for Predicting Solitary Pulmonary Nodule Malignancy in Patients Undergoing PET/CT Examination
Ioannis D. Apostolopoulos, Νικόλαος Παπαθανασίου, D. Apostolopoulos, et al.
Big Data and Cognitive Computing (2024) Vol. 8, Iss. 8, pp. 85-85
Open Access
Between Two Worlds: Investigating the Intersection of Human Expertise and Machine Learning in the Case of Coronary Artery Disease Diagnosis
Ioannis D. Apostolopoulos, Νικόλαος Παπανδριανός, Dimitrios Apostolopoulos, et al.
Bioengineering (2024) Vol. 11, Iss. 10, pp. 957-957
Open Access
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