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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:

Application of Artificial Intelligence in Lung Cancer
Hwa‐Yen Chiu, Heng‐Sheng Chao, Yuh‐Min Chen
Cancers (2022) Vol. 14, Iss. 6, pp. 1370-1370
Open Access | Times Cited: 70

Showing 1-25 of 70 citing articles:

Artificial Intelligence in Pharmaceutical and Healthcare Research
Subrat Kumar Bhattamisra, Priyanka Banerjee, Pratibha Gupta, et al.
Big Data and Cognitive Computing (2023) Vol. 7, Iss. 1, pp. 10-10
Open Access | Times Cited: 94
Advances of Artificial Intelligence in Anti-Cancer Drug Design: A Review of the Past Decade
Liuying Wang, Yongzhen Song, Hesong Wang, et al.
Pharmaceuticals (2023) Vol. 16, Iss. 2, pp. 253-253
Open Access | Times Cited: 48
Shaping the future of AI in healthcare through ethics and governance
Rabaï Bouderhem
Humanities and Social Sciences Communications (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 20
Deep Machine Learning for Medical Diagnosis, Application to Lung Cancer Detection: A Review
Hadrien T. Gayap, Moulay A. Akhloufi
BioMedInformatics (2024) Vol. 4, Iss. 1, pp. 236-284
Open Access | Times Cited: 16
Artificial Intelligence in Lung Cancer Imaging: Unfolding the Future
Michaela Cellina, Maurizio Cè, Giovanni Irmici, et al.
Diagnostics (2022) Vol. 12, Iss. 11, pp. 2644-2644
Open Access | Times Cited: 44
Artificial Intelligence and Lung Cancer: Impact on Improving Patient Outcomes
Zainab Gandhi, Priyatham Gurram, Birendra Amgai, et al.
Cancers (2023) Vol. 15, Iss. 21, pp. 5236-5236
Open Access | Times Cited: 30
Unveiling the potential of proteomic and genetic signatures for precision therapeutics in lung cancer management
Shriyansh Srivastava, Nandani Jayaswal, Sachin Kumar, et al.
Cellular Signalling (2023) Vol. 113, pp. 110932-110932
Closed Access | Times Cited: 19
Recent advances in lung cancer research: unravelling the future of treatment
Luca Bertolaccini, Monica Casiraghi, Clarissa Uslenghi, et al.
Updates in Surgery (2024) Vol. 76, Iss. 6, pp. 2129-2140
Closed Access | Times Cited: 9
Immunotherapy for lung cancer
Girshani Sathish, L.K. Monavarshini, Keerthi Sundaram, et al.
Pathology - Research and Practice (2024) Vol. 254, pp. 155104-155104
Closed Access | Times Cited: 6
Cancer Detection Using Artificial Intelligence: A Paradigm in Early Diagnosis
Gayathri Bulusu, K. E. Ch. Vidyasagar, Malini Mudigonda, et al.
Archives of Computational Methods in Engineering (2025)
Open Access
Integrated Model (IM- LTS) for Lung Tumor Segmentation using Neural Networks and IoMT].
J. Jayapradha, Su-Cheng Haw, Palanichamy Naveen, et al.
MethodsX (2025), pp. 103201-103201
Closed Access
Imaging Diagnosis of Hepatocellular Carcinoma: A State-of-the-Art Review
Gianvito Candita, Sara Rossi, Karolina Cwiklinska, et al.
Diagnostics (2023) Vol. 13, Iss. 4, pp. 625-625
Open Access | Times Cited: 18
The use of artificial intelligence tools in cancer detection compared to the traditional diagnostic imaging methods: An overview of the systematic reviews
Helbert Eustáquio Cardoso da Silva, Gláucia Nize Martins Santos, André Ferreira Leite, et al.
PLoS ONE (2023) Vol. 18, Iss. 10, pp. e0292063-e0292063
Open Access | Times Cited: 18
Combined model integrating deep learning, radiomics, and clinical data to classify lung nodules at chest CT
Chia-Ying Lin, Shu‐Mei Guo, Jenn-Jier James Lien, et al.
La radiologia medica (2023) Vol. 129, Iss. 1, pp. 56-69
Open Access | Times Cited: 18
Multi-Layered Non-Local Bayes Model for Lung Cancer Early Diagnosis Prediction with the Internet of Medical Things
Yossra H. Ali, C. Seelammal, Raja Marappan, et al.
Bioengineering (2023) Vol. 10, Iss. 2, pp. 138-138
Open Access | Times Cited: 15
Why artificial intelligence needs to understand consequences
Neil Savage
Nature (2023)
Closed Access | Times Cited: 14
A Holistic Approach to Implementing Artificial Intelligence in Lung Cancer
Seyed Masoud HaghighiKian, Ahmad Shirinzadeh-Dastgiri, Mohammad Vakili-Ojarood, et al.
Indian Journal of Surgical Oncology (2024)
Closed Access | Times Cited: 5
Diagnostic test accuracy of artificial intelligence-based imaging for lung cancer screening: A systematic review and meta-analysis
Lay Teng Thong, Hui Shan Chou, Han Shi Jocelyn Chew, et al.
Lung Cancer (2022) Vol. 176, pp. 4-13
Closed Access | Times Cited: 21
Machine Learning and Texture Analysis of [18F]FDG PET/CT Images for the Prediction of Distant Metastases in Non-Small-Cell Lung Cancer Patients
Armin Hakkak Moghadam Torbati, Sara Pellegrino, Rosa Fonti, et al.
Biomedicines (2024) Vol. 12, Iss. 3, pp. 472-472
Open Access | Times Cited: 3
A new model using deep learning to predict recurrence after surgical resection of lung adenocarcinoma
Hong‐Gee Kim, Hee Sang Hwang, Gyuheon Choi, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 3
The Role of Genomics and Proteomics in Lung Cancer Early Detection and Treatment
Mohammad Hadi Abbasian, Ali M. Ardekani, Navid Sobhani, et al.
Cancers (2022) Vol. 14, Iss. 20, pp. 5144-5144
Open Access | Times Cited: 19
Lung cancer histopathological image classification using wavelets and AlexNet
Prabira Kumar Sethy, A. Geetha Devi, Bikash Padhan, et al.
Journal of X-Ray Science and Technology (2022) Vol. 31, Iss. 1, pp. 211-221
Closed Access | Times Cited: 18
Deep learning‐based classification and spatial prognosis risk score on whole‐slide images of lung adenocarcinoma
Hanlin Ding, Yipeng Feng, Xing Huang, et al.
Histopathology (2023) Vol. 83, Iss. 2, pp. 211-228
Closed Access | Times Cited: 9
See Lung Cancer with an AI
Joanna Bidzińska, Edyta Szurowska
Cancers (2023) Vol. 15, Iss. 4, pp. 1321-1321
Open Access | Times Cited: 8
New research progress on 18F-FDG PET/CT radiomics for EGFR mutation prediction in lung adenocarcinoma: a review
Xinyu Ge, Jianxiong Gao, Rong Niu, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 8
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