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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:

Machine learning models to predict the relationship between printing parameters and tensile strength of 3D Poly (lactic acid) scaffolds for tissue engineering applications
Duygu Ege, Seda Sertturk, Berk Acarkan, et al.
Biomedical Physics & Engineering Express (2023) Vol. 9, Iss. 6, pp. 065014-065014
Open Access | Times Cited: 18

Showing 18 citing articles:

A comprehensive review on fillers and mechanical properties of 3D printed polymer composites
Nishtha Arora, Sachin Dua, Vivek Kumar Singh, et al.
Materials Today Communications (2024) Vol. 40, pp. 109617-109617
Closed Access | Times Cited: 11
Artificial Intelligence‐Augmented Additive Manufacturing: Insights on Closed‐Loop 3D Printing
Abdul Rahman Sani, Ali Zolfagharian, Abbas Z. Kouzani
Advanced Intelligent Systems (2024)
Open Access | Times Cited: 10
Enhancing quality control in bioprinting through machine learning
Amedeo Franco Bonatti, Giovanni Vozzi, Carmelo De Maria
Biofabrication (2024) Vol. 16, Iss. 2, pp. 022001-022001
Closed Access | Times Cited: 8
A comparative review of multi-axis 3D printing
Yuan Yao, Longyu Cheng, Zhengyu Li
Journal of Manufacturing Processes (2024) Vol. 120, pp. 1002-1022
Closed Access | Times Cited: 7
AI-driven 3D bioprinting for regenerative medicine: From bench to bedside
Huajin Zhang, Xianhao Zhou, Yongcong Fang, et al.
Bioactive Materials (2024) Vol. 45, pp. 201-230
Closed Access | Times Cited: 6
Micromechanical Models for FDM 3D-Printed Polymers: A Review
Rowin J.M. Bol, Branko Šavija
Polymers (2023) Vol. 15, Iss. 23, pp. 4497-4497
Open Access | Times Cited: 13
Machine learning-assisted prediction modeling for anisotropic flexural strength variations in fused filament fabrication of graphene reinforced poly-lactic acid composites
Tapish Raj, Amrit Tiwary, Akash Jain, et al.
Progress in Additive Manufacturing (2024)
Closed Access | Times Cited: 4
3D Bioprinting of Natural Materials and Their AI-Enhanced Printability: A Review
Soumaya Grira, Mohammad Sayem Mozumder, Abdel‐Hamid I. Mourad, et al.
Bioprinting (2025), pp. e00385-e00385
Closed Access
Structural integrity of fused filament fabricated polymer composites using Taguchi method and XGB regression
Akash Jain, Tapish Raj, Saloni Upadhyay, et al.
Proceedings of the Institution of Mechanical Engineers Part N Journal of Nanomaterials Nanoengineering and Nanosystems (2025)
Closed Access
Role of artificial intelligence in data-centric additive manufacturing processes for biomedical applications
Saman Mohammadnabi, Nima Moslemy, Hadi Taghvaei, et al.
Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials (2025) Vol. 166, pp. 106949-106949
Closed Access
A machine learning approach to refining surface quality and material durability in additive manufacturing
Siva Surya Mulugundam, Santhosh Kumar Gugulothu, M Varshith
Progress in Additive Manufacturing (2025)
Closed Access
XGB Modeling Reveals Improvement of Compressive Strength of Cement-Based Composites with Addition of HPMC and Chitosan
Duygu Ege, Ali Reza Kamali
Materials (2024) Vol. 17, Iss. 2, pp. 374-374
Open Access | Times Cited: 3
Mapping Biomaterial Complexity by Machine Learning
Eman Ahmed, Prajakatta Mulay, César E. Ramírez, et al.
Tissue Engineering Part A (2024) Vol. 30, Iss. 19-20, pp. 662-680
Closed Access | Times Cited: 3
Machine learning-driven prediction of tensile strength in 3D-printed PLA parts
Mohammad Hossein Nikzad, Mohammad Heidari‐Rarani, Reza Rasti, et al.
Expert Systems with Applications (2024), pp. 125836-125836
Closed Access | Times Cited: 3
Investigating the Effect of Processing and Material Parameters of Alginate Dialdehyde-Gelatin (ADA-GEL)-Based Hydrogels on Stiffness by XGB Machine Learning Model
Duygu Ege, Aldo R. Boccaccını
Bioengineering (2024) Vol. 11, Iss. 5, pp. 415-415
Open Access | Times Cited: 2
A novel systematically optimized tabular neural network (TabNet) algorithm for predicting the tensile modulus of additively manufactured PLA parts
Mohammad Hossein Nikzad, Mohammad Heidari‐Rarani, Reza Rasti
Materials Today Communications (2024) Vol. 41, pp. 110442-110442
Closed Access | Times Cited: 2
Investigation of effect of processing parameters of 3D printed NHS/EDC crosslinked carboxy methyl cellulose/gelatin hydrogels with machine learning techniques
Duygu Ege, Şule Arıcı
Materials Research Express (2024) Vol. 11, Iss. 4, pp. 045304-045304
Open Access | Times Cited: 1
Long-short-term memory (LSTM)-based modeling of the stiffness of 3D-printed PLA parts
Mohammad Hossein Nikzad, Mohammad Heidari‐Rarani, Reza Rasti
Materials Letters (2024) Vol. 379, pp. 137636-137636
Closed Access | Times Cited: 1
Predictive modelling of flexural behaviour of polymer composites: a machine learning approach through material extrusion
Akash Jain, Saloni Upadhyay, Kanishka Pathik, et al.
Progress in Additive Manufacturing (2024)
Closed Access | Times Cited: 1
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