Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

An updated systematic review of radiomics in osteosarcoma: utilizing CLAIM to adapt the increasing trend of deep learning application in radiomics
Jingyu Zhong, Yangfan Hu, Guangcheng Zhang, et al.
Insights into Imaging (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 13

Showing 13 citing articles:

An overview of meta-analyses on radiomics: more evidence is needed to support clinical translation
Jingyu Zhong, Junjie Lu, Guangcheng Zhang, et al.
Insights into Imaging (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 19
Self-reporting with checklists in artificial intelligence research on medical imaging: a systematic review based on citations of CLAIM
Burak Koçak, Ali Keleş, Tugba Akinci D’Antonoli
European Radiology (2023) Vol. 34, Iss. 4, pp. 2805-2815
Closed Access | Times Cited: 14
Multimodal Imaging of Osteosarcoma: From First Diagnosis to Radiomics
Maurizio Cè, Michaela Cellina, Thirapapha Ueanukul, et al.
Cancers (2025) Vol. 17, Iss. 4, pp. 599-599
Open Access
Enhanced boundary-directed lightweight approach for digital pathological image analysis in critical oncological diagnostics
Ou Luo, Jing Zhou, Fangfang Gou
Journal of X-Ray Science and Technology (2025)
Closed Access
The endorsement of general and artificial intelligence reporting guidelines in radiological journals: a meta-research study
Jingyu Zhong, Yue Xing, Junjie Lu, et al.
BMC Medical Research Methodology (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 7
Magnetic Resonance Imaging Texture Analysis Based on Intraosseous and Extraosseous Lesions to Predict Prognosis in Patients with Osteosarcoma
Yu Mori, Hainan Ren, Naoko Mori, et al.
Diagnostics (2024) Vol. 14, Iss. 22, pp. 2562-2562
Open Access | Times Cited: 2
Artificial intelligence in predicting recurrence after first-line treatment of liver cancer: a systematic review and meta-analysis
Linyong Wu, Qingfeng Lai, Songhua Li, et al.
BMC Medical Imaging (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 1
Development of the interpretable typing prediction model for osteosarcoma and chondrosarcoma based on machine learning and radiomics: a multicenter retrospective study
Qing-Yuan Long, Fengyan Wang, Yue Hu, et al.
Frontiers in Medicine (2024) Vol. 11
Open Access | Times Cited: 1
Prediction of response to preoperative neoadjuvant chemotherapy in extremity high-grade osteosarcoma using X-ray and multiparametric MRI radiomics
Zhendong Luo, Jing Li, Yuting Liao, et al.
Journal of X-Ray Science and Technology (2023) Vol. 31, Iss. 3, pp. 611-626
Closed Access | Times Cited: 3
Reporting Quality of Research Studies on AI Applications in Medical Images According to the CLAIM Guidelines in a Radiology Journal With a Strong Prominence in Asia
D. Kim, Hyun Woo Oh, Chong Hyun Suh
Korean Journal of Radiology (2023) Vol. 24, Iss. 12, pp. 1179-1179
Open Access | Times Cited: 3
A systematic review of radiomics in giant cell tumor of bone (GCTB): the potential of analysis on individual radiomics feature for identifying genuine promising imaging biomarkers
Jingyu Zhong, Yue Xing, Guangcheng Zhang, et al.
Journal of Orthopaedic Surgery and Research (2023) Vol. 18, Iss. 1
Open Access | Times Cited: 2
Robust hyperparameter tuned deep Elman neural network for the diagnosis of osteosarcoma on histology images
S. Prabakaran, S. Praveena
Journal of Intelligent & Fuzzy Systems (2023) Vol. 45, Iss. 4, pp. 5987-6003
Closed Access | Times Cited: 2
Preoperative prediction of high-grade osteosarcoma response to neoadjuvant therapy based on a plain CT radiomics model: A dual-center study
Fan Yang, Ying Feng, Pengfei Sun, et al.
Journal of bone oncology (2024) Vol. 47, pp. 100614-100614
Open Access
A systematic review of deep learning-based spinal bone lesion detection in medical images
Bianca Teodorescu, Leonard Gilberg, Philip William Melton, et al.
Acta Radiologica (2024) Vol. 65, Iss. 9, pp. 1115-1125
Closed Access
Page 1

Scroll to top