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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–Based MRI Texture Analysis to Predict the Histologic Grade of Oral Squamous Cell Carcinoma
Jiliang Ren, Meng Qi, Ying Yuan, et al.
American Journal of Roentgenology (2020) Vol. 215, Iss. 5, pp. 1184-1190
Closed Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

Comparison of nomogram with machine learning techniques for prediction of overall survival in patients with tongue cancer
Rasheed Omobolaji Alabi, Antti Mäkitie, Matti Pirinen, et al.
International Journal of Medical Informatics (2020) Vol. 145, pp. 104313-104313
Closed Access | Times Cited: 70
Prediction models applying machine learning to oral cavity cancer outcomes: A systematic review
John Adeoye, Jia Tan, S. W. Choi, et al.
International Journal of Medical Informatics (2021) Vol. 154, pp. 104557-104557
Closed Access | Times Cited: 58
Machine learning in dental, oral and craniofacial imaging: a review of recent progress
Ruiyang Ren, Haozhe Luo, Chongying Su, et al.
PeerJ (2021) Vol. 9, pp. e11451-e11451
Open Access | Times Cited: 52
Machine-Learning Applications in Oral Cancer: A Systematic Review
Xaviera A. López-Cortés, Felipe Matamala, Bernardo Venegas, et al.
Applied Sciences (2022) Vol. 12, Iss. 11, pp. 5715-5715
Open Access | Times Cited: 32
Data-centric artificial intelligence in oncology: a systematic review assessing data quality in machine learning models for head and neck cancer
John Adeoye, Liuling Hui, Yu‐Xiong Su
Journal Of Big Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 19
MRI radiomics to monitor therapeutic outcome of sorafenib plus IHA transcatheter NK cell combination therapy in hepatocellular carcinoma
Guangbo Yu, Zigeng Zhang, Aydιn Eresen, et al.
Journal of Translational Medicine (2024) Vol. 22, Iss. 1
Open Access | Times Cited: 7
Machine learning-based MRI radiomics for assessing the level of tumor infiltrating lymphocytes in oral tongue squamous cell carcinoma: a pilot study
Jiliang Ren, Gongxin Yang, Yang Song, et al.
BMC Medical Imaging (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 5
An Intelligent Multisampling Tensor Model for Oral Cancer Classification
Chenxi Huang, Guokai Zhang, Sirui Chen, et al.
IEEE Transactions on Industrial Informatics (2022) Vol. 18, Iss. 11, pp. 7853-7861
Closed Access | Times Cited: 14
Early predicting tribocorrosion rate of dental implant titanium materials using random forest machine learning models
Remya Ampadi Ramachandran, Valentim Adelino Ricardo Barão, Didem Ozevin, et al.
Tribology International (2023) Vol. 187, pp. 108735-108735
Open Access | Times Cited: 8
Enhanced Diagnostic Precision: Assessing Tumor Differentiation in Head and Neck Squamous Cell Carcinoma Using Multi-Slice Spiral CT Texture Analysis
Lays Assolini Pinheiro de Oliveira, Diana Lorena Garcia Lopes, João Pedro Perez Gomes, et al.
Journal of Clinical Medicine (2024) Vol. 13, Iss. 14, pp. 4038-4038
Open Access | Times Cited: 2
Integration of IDPC Clustering Analysis and Interpretable Machine Learning for Survival Risk Prediction of Patients with ESCC
Dan Ling, Anhao Liu, Junwei Sun, et al.
Interdisciplinary Sciences Computational Life Sciences (2023) Vol. 15, Iss. 3, pp. 480-498
Closed Access | Times Cited: 5
Texture Feature‐Based Machine Learning Classification on MRI Image for Sepsis‐Associated Encephalopathy Detection: A Pilot Study
Xiao Mo, Xin Xiong, Yijie Wang, et al.
Computational and Mathematical Methods in Medicine (2023) Vol. 2023, Iss. 1
Open Access | Times Cited: 4
Development of a flexible feature selection framework in radiomics-based prediction modeling: Assessment with four real-world datasets
Sung-Soo Hong, Sungjun Hong, Eunsun Oh, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
BID-Net: An Automated System for Bone Invasion Detection Occurring at Stage T4 in Oral Squamous Carcinoma Using Deep Learning
Pinky Agarwal, Anju Yadav, Pratistha Mathur, et al.
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-11
Open Access | Times Cited: 7
Application of machine learning in oral and maxillofacial surgery
Kaixin Yan, Lei Liu, Hui Li
Artificial Intelligence in Medical Imaging (2021) Vol. 2, Iss. 6, pp. 104-114
Open Access | Times Cited: 8
Whole-tumor histogram analysis of apparent diffusion coefficient maps with machine learning algorithms for predicting histologic grade of sinonasal squamous cell carcinoma: a preliminary study
Yue Geng, Rujian Hong, Yu‐Shu Cheng, et al.
European Archives of Oto-Rhino-Laryngology (2023) Vol. 280, Iss. 9, pp. 4131-4140
Closed Access | Times Cited: 3
An MRI-based radiomics nomogram for detecting cervical esophagus invasion in hypopharyngeal squamous cell carcinoma
Meng Qi, Yan Sha, Duo Zhang, et al.
Cancer Imaging (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 3
Efficacy of magnetic resonance imaging texture features of the lateral pterygoid muscle in distinguishing rheumatoid arthritis and osteoarthritis of the temporomandibular joint
Hirotaka Muraoka, Takashi Kaneda, Naohisa Hirahara, et al.
Dentomaxillofacial Radiology (2023) Vol. 52, Iss. 3
Open Access | Times Cited: 2
The Classification of Oral Squamous Cell Carcinoma (OSCC) by Means of Transfer Learning
Ahmad Ridhauddin Abdul Rauf, Wan Hasbullah Mohd Isa, Ismail Mohd Khairuddin, et al.
Lecture notes in networks and systems (2022), pp. 386-391
Closed Access | Times Cited: 4
Interobserver delineation variability of computed tomography-based radiomic features of the parotid gland
Kanyapat Buasawat, Sasikarn Chamchod, Todsaporn Fuangrod, et al.
Radiation Oncology Journal (2024) Vol. 42, Iss. 1, pp. 63-73
Open Access
Application of Artificial Intelligence in Head and Neck Imaging
Ling Zhu, Xiaoqing Dai, Jiliang Ren, et al.
(2024), pp. 145-152
Closed Access
Assessing the Reporting Quality of Machine Learning Algorithms in Head and Neck Oncology
Rahul Alapati, Bryan Renslo, Sarah F. Wagoner, et al.
The Laryngoscope (2024) Vol. 135, Iss. 2, pp. 687-694
Closed Access
Image-based multi-omics analysis for oral science: recent progress and perspectives
Yizhuo Chen, Pengxi Du, Yinyin Zhang, et al.
Journal of Dentistry (2024), pp. 105425-105425
Closed Access
Impact of Machine Learning and Prediction Models in the Diagnosis of Oral Health Conditions
Nihar Ranjan Panda, Soumya Subhashree Satapathy, Sanat Kumar Bhuyan, et al.
International Journal of Statistics in Medical Research (2023) Vol. 12, pp. 51-57
Open Access | Times Cited: 1
Choise of Statistical Processing Methods for the Results of Radcomic Analysis of CT Images of Head and Neck Tumors
Aziz Pattokhov, Yu. M. Khodjibekova, Marat Khodjibekov
Medical Radiology and radiation safety (2023) Vol. 68, Iss. 3, pp. 52-56
Open Access
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