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:
Development and Validation of Multi-Omics Thymoma Risk Classification Model Based on Transfer Learning
Wei Liu, Wei Wang, Hanyi Zhang, et al.
Journal of Digital Imaging (2023) Vol. 36, Iss. 5, pp. 2015-2024
Open Access | Times Cited: 9
Wei Liu, Wei Wang, Hanyi Zhang, et al.
Journal of Digital Imaging (2023) Vol. 36, Iss. 5, pp. 2015-2024
Open Access | Times Cited: 9
Showing 9 citing articles:
Hybrid Approach to Classifying Histological Subtypes of Non-small Cell Lung Cancer (NSCLC): Combining Radiomics and Deep Learning Features from CT Images
Geon Oh, Yongha Gi, Jeongshim Lee, et al.
Deleted Journal (2025)
Closed Access | Times Cited: 1
Geon Oh, Yongha Gi, Jeongshim Lee, et al.
Deleted Journal (2025)
Closed Access | Times Cited: 1
Multi-dimensional interpretable deep learning-radiomics based on intra-tumoral and spatial habitat for preoperative prediction of thymic epithelial tumours risk categorisation
Yuhua Yang, Jia Cheng, Can Cui, et al.
Acta Oncologica (2025) Vol. 64, pp. 391-405
Open Access
Yuhua Yang, Jia Cheng, Can Cui, et al.
Acta Oncologica (2025) Vol. 64, pp. 391-405
Open Access
Radiomics in thymic epithelial tumors: a scoping review of current status and advances
Xiaolian Wang, Pei Huang, Z Wang, et al.
BMC Cancer (2025) Vol. 25, Iss. 1
Open Access
Xiaolian Wang, Pei Huang, Z Wang, et al.
BMC Cancer (2025) Vol. 25, Iss. 1
Open Access
Identification and risk classification of thymic epithelial tumors using 3D computed tomography images and deep learning models
Ye Sung Moon, Byunggeon Park, Jongmin Park, et al.
Biomedical Signal Processing and Control (2024) Vol. 95, pp. 106473-106473
Closed Access | Times Cited: 2
Ye Sung Moon, Byunggeon Park, Jongmin Park, et al.
Biomedical Signal Processing and Control (2024) Vol. 95, pp. 106473-106473
Closed Access | Times Cited: 2
Predicting the risk category of thymoma with machine learning-based computed tomography radiomics signatures and their between-imaging phase differences
Liang Zhu, Jiamin Li, Yi-Han Tang, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
Liang Zhu, Jiamin Li, Yi-Han Tang, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
A machine learning based on CT radiomics signature and change value features for predicting the risk classification of thymoma
Liang Zhu, Jiaming Li, Yi-Han Tang, et al.
Research Square (Research Square) (2024)
Open Access
Liang Zhu, Jiaming Li, Yi-Han Tang, et al.
Research Square (Research Square) (2024)
Open Access
Applying Machine Learning Techniques to Time Series Analysis for Early Detection of Thymoma
M N Nachappa, Sachin Goswami, Shreshta Bandhu Rastogi
(2024), pp. 1-6
Closed Access
M N Nachappa, Sachin Goswami, Shreshta Bandhu Rastogi
(2024), pp. 1-6
Closed Access
Integrated analysis of -omic landscapes in breast cancer subtypes
Suren Davitavyan, Gevorg Martirosyan, Gohar Mkrtchyan, et al.
F1000Research (2024) Vol. 13, pp. 564-564
Open Access
Suren Davitavyan, Gevorg Martirosyan, Gohar Mkrtchyan, et al.
F1000Research (2024) Vol. 13, pp. 564-564
Open Access
Multimodal MRI-based deep-radiomics model predicts response in cervical cancer treated with neoadjuvant chemoradiotherapy
Zhihua Cai, Sang Li, Zhuang Xiong, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
Zhihua Cai, Sang Li, Zhuang Xiong, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
