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:
The application of radiomics machine learning models based on multimodal MRI with different sequence combinations in predicting cervical lymph node metastasis in oral tongue squamous cell carcinoma patients
Sheng Liu, Aihua Zhang, Jianjun Xiong, et al.
Head & Neck (2023) Vol. 46, Iss. 3, pp. 513-527
Closed Access | Times Cited: 6
Sheng Liu, Aihua Zhang, Jianjun Xiong, et al.
Head & Neck (2023) Vol. 46, Iss. 3, pp. 513-527
Closed Access | Times Cited: 6
Showing 6 citing articles:
Artificial intelligence in otorhinolaryngology: current trends and application areas
Emre Demir, Burak Numan Uğurlu, Gülay Aktar Uğurlu, et al.
European Archives of Oto-Rhino-Laryngology (2025)
Open Access | Times Cited: 1
Emre Demir, Burak Numan Uğurlu, Gülay Aktar Uğurlu, et al.
European Archives of Oto-Rhino-Laryngology (2025)
Open Access | Times Cited: 1
Application of CT and MRI images based on artificial intelligence to predict lymph node metastases in patients with oral squamous cell carcinoma: a subgroup meta-analysis
Cheng Deng, Jun Hu, Ping Tang, et al.
Frontiers in Oncology (2024) Vol. 14
Open Access | Times Cited: 1
Cheng Deng, Jun Hu, Ping Tang, et al.
Frontiers in Oncology (2024) Vol. 14
Open Access | Times Cited: 1
A novel nomogram for predicting overall survival in patients with tongue squamous cell carcinoma using clinical features and MRI radiomics data: a pilot study
Yongling Yao, Xin Jin, Tianfang Peng, et al.
World Journal of Surgical Oncology (2024) Vol. 22, Iss. 1
Open Access
Yongling Yao, Xin Jin, Tianfang Peng, et al.
World Journal of Surgical Oncology (2024) Vol. 22, Iss. 1
Open 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
Rahul Alapati, Bryan Renslo, Sarah F. Wagoner, et al.
The Laryngoscope (2024) Vol. 135, Iss. 2, pp. 687-694
Closed Access
Adrenal indeterminate nodules: CT-based radiomics analysis of different machine learning models for predicting adrenal metastases in lung cancer patients
Lixiu Cao, Haoxuan Yang, Huijing Wu, et al.
Frontiers in Oncology (2024) Vol. 14
Open Access
Lixiu Cao, Haoxuan Yang, Huijing Wu, et al.
Frontiers in Oncology (2024) Vol. 14
Open Access
The application of nomogram model integrating clinical factors and multi-modal MRI radiomics features for predicting cervical lymph nodes metastasis for patients with oral tongue squamous cell carcinoma: a multicenter study
Sheng Liu, Jianjun Xiong, Aihua Zhang, et al.
Research Square (Research Square) (2024)
Open Access
Sheng Liu, Jianjun Xiong, Aihua Zhang, et al.
Research Square (Research Square) (2024)
Open Access
