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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:

Network-based machine learning approach to predict immunotherapy response in cancer patients
JungHo Kong, Doyeon Ha, Juhun Lee, et al.
Nature Communications (2022) Vol. 13, Iss. 1
Open Access | Times Cited: 129

Showing 1-25 of 129 citing articles:

Immune checkpoint therapy—current perspectives and future directions
Padmanee Sharma, Sangeeta Goswami, Deblina Raychaudhuri, et al.
Cell (2023) Vol. 186, Iss. 8, pp. 1652-1669
Closed Access | Times Cited: 459
Artificial intelligence for predictive biomarker discovery in immuno-oncology: a systematic review
Arsela Prelaj, Vanja Mišković, Michele Zanitti, et al.
Annals of Oncology (2023) Vol. 35, Iss. 1, pp. 29-65
Open Access | Times Cited: 100
Defining clinically useful biomarkers of immune checkpoint inhibitors in solid tumours
Ashley M. Holder, Aikaterini Dedeilia, Kailan Sierra-Davidson, et al.
Nature reviews. Cancer (2024) Vol. 24, Iss. 7, pp. 498-512
Closed Access | Times Cited: 62
Immune-checkpoint inhibitor resistance in cancer treatment: Current progress and future directions
Chenyue Zhang, Chenxing Zhang, Haiyong Wang
Cancer Letters (2023) Vol. 562, pp. 216182-216182
Closed Access | Times Cited: 56
When Machine Learning Meets 2D Materials: A Review
Bin Lu, Yuze Xia, Yuqian Ren, et al.
Advanced Science (2024) Vol. 11, Iss. 13
Open Access | Times Cited: 47
Application of artificial intelligence for improving early detection and prediction of therapeutic outcomes for gastric cancer in the era of precision oncology
Zhe Wang, Yang Liu, Xing Niu
Seminars in Cancer Biology (2023) Vol. 93, pp. 83-96
Closed Access | Times Cited: 45
Informing immunotherapy with multi-omics driven machine learning
Yawei Li, Wu Xin, Deyu Fang, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 24
Liquid biopsy for human cancer: cancer screening, monitoring, and treatment
Hao Wang, Yi Zhang, Hao Zhang, et al.
MedComm (2024) Vol. 5, Iss. 6
Open Access | Times Cited: 21
Current and future directions in network biology
Marinka Žitnik, Michelle M. Li, A. V. Wells, et al.
Bioinformatics Advances (2024) Vol. 4, Iss. 1
Open Access | Times Cited: 19
Combined Machine Learning and High-Throughput Calculations Predict Heyd–Scuseria–Ernzerhof Band Gap of 2D Materials and Potential MoSi2N4 Heterostructures
Weibin Zhang, Jie Guo, Xiankui Lv, et al.
The Journal of Physical Chemistry Letters (2024) Vol. 15, Iss. 20, pp. 5413-5419
Closed Access | Times Cited: 17
Non-small cell lung cancer patients treated with Anti-PD1 immunotherapy show distinct microbial signatures and metabolic pathways according to progression-free survival and PD-L1 status
Dávid Dóra, Balázs Ligeti, Tamás Kovács, et al.
OncoImmunology (2023) Vol. 12, Iss. 1
Open Access | Times Cited: 28
Artificial intelligence in cancer immunotherapy: Applications in neoantigen recognition, antibody design and immunotherapy response prediction
Li Tong, Yupeng Li, Xiaoyi Zhu, et al.
Seminars in Cancer Biology (2023) Vol. 91, pp. 50-69
Closed Access | Times Cited: 26
Machine learning for prediction of immunotherapeutic outcome in non-small-cell lung cancer based on circulating cytokine signatures
Feifei Wei, Koichi Azuma, Yoshiro Nakahara, et al.
Journal for ImmunoTherapy of Cancer (2023) Vol. 11, Iss. 7, pp. e006788-e006788
Open Access | Times Cited: 26
Biomedical Big Data Technologies, Applications, and Challenges for Precision Medicine: A Review
Xue Yang, Kexin Huang, Dewei Yang, et al.
Global Challenges (2023) Vol. 8, Iss. 1
Open Access | Times Cited: 26
Current Understanding on Why Ovarian Cancer Is Resistant to Immune Checkpoint Inhibitors
Anna Pawłowska, Anna K. Rekowska, Weronika Kuryło, et al.
International Journal of Molecular Sciences (2023) Vol. 24, Iss. 13, pp. 10859-10859
Open Access | Times Cited: 25
Peptide Hydrogels as Immunomaterials and Their Use in Cancer Immunotherapy Delivery
Natashya Falcone, Menekşe Ermis, Dilara Goksu Tamay, et al.
Advanced Healthcare Materials (2023) Vol. 12, Iss. 27
Closed Access | Times Cited: 24
Potential of CDC25 phosphatases in cancer research and treatment: key to precision medicine
Ibraheem Dakilah, Amani A. Harb, Eman Abu‐Gharbieh, et al.
Frontiers in Pharmacology (2024) Vol. 15
Open Access | Times Cited: 10
Advancing precision cancer immunotherapy drug development, administration, and response prediction with AI-enabled Raman spectroscopy
Jay Chadokiya, Kai Chang, Saurabh Sharma, et al.
Frontiers in Immunology (2025) Vol. 15
Open Access | Times Cited: 1
Advancements in immunotherapy for gastric cancer: Unveiling the potential of immune checkpoint inhibitors and emerging strategies
Jiawei Song, Jun Zhu, Yu Jiang, et al.
Biochimica et Biophysica Acta (BBA) - Reviews on Cancer (2025) Vol. 1880, Iss. 2, pp. 189277-189277
Closed Access | Times Cited: 1
Microfluidic technologies for enhancing the potency, predictability and affordability of adoptive cell therapies
Zongjie Wang, Shana O. Kelley
Nature Biomedical Engineering (2025)
Closed Access | Times Cited: 1
Cell-cell communication network-based interpretable machine learning predicts cancer patient response to immune checkpoint inhibitors
Juhun Lee, Donghyo Kim, JungHo Kong, et al.
Science Advances (2024) Vol. 10, Iss. 5
Open Access | Times Cited: 6
Recent Advances in Melanoma Diagnosis and Prognosis Using Machine Learning Methods
Sarah Grossarth, Dominique Mosley, Christopher Madden, et al.
Current Oncology Reports (2023) Vol. 25, Iss. 6, pp. 635-645
Open Access | Times Cited: 15
Biological knowledge graph-guided investigation of immune therapy response in cancer with graph neural network
Lianhe Zhao, Xiaoning Qi, Yang Chen, et al.
Briefings in Bioinformatics (2023) Vol. 24, Iss. 2
Closed Access | Times Cited: 13
Using Machine Learning to Predict Surgical Site Infection After Lumbar Spine Surgery
Tianyou Chen, Chong Liu, Zide Zhang, et al.
Infection and Drug Resistance (2023) Vol. Volume 16, pp. 5197-5207
Open Access | Times Cited: 13
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