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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:

Cascaded Wx: A Novel Prognosis-Related Feature Selection Framework in Human Lung Adenocarcinoma Transcriptomes
Bonggun Shin, Sung Soo Park, Ji Hyung Hong, et al.
Frontiers in Genetics (2019) Vol. 10
Open Access | Times Cited: 11

Showing 11 citing articles:

Deep learning for survival analysis: a review
Simon Wiegrebe, Philipp Kopper, Raphael Sonabend, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 3
Open Access | Times Cited: 51
Recent advancements in deep learning based lung cancer detection: A systematic review
Shubham Dodia, B. Annappa, P A Mahesh
Engineering Applications of Artificial Intelligence (2022) Vol. 116, pp. 105490-105490
Closed Access | Times Cited: 47
A multi-parameterized artificial neural network for lung cancer risk prediction
Gregory R. Hart, David A. Roffman, Roy H. Decker, et al.
PLoS ONE (2018) Vol. 13, Iss. 10, pp. e0205264-e0205264
Open Access | Times Cited: 67
A convolutional neural network model for survival prediction based on prognosis-related cascaded Wx feature selection
Qingyan Yin, Wangwang Chen, Chunxia Zhang, et al.
Laboratory Investigation (2022) Vol. 102, Iss. 10, pp. 1064-1074
Closed Access | Times Cited: 35
Diagnostic and Therapeutic Implications of microRNAs in Non-Small Cell Lung Cancer
Young‐Ho Ahn, Yoon Ho Ko
International Journal of Molecular Sciences (2020) Vol. 21, Iss. 22, pp. 8782-8782
Open Access | Times Cited: 36
AI/ML advances in non-small cell lung cancer biomarker discovery
Minal Çalışkan, Koichi Tazaki
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 6
Mathematical and Machine Learning Models of Renal Cell Carcinoma: A Review
Dilruba Sofia, Q. Zhou, Leili Shahriyari
Bioengineering (2023) Vol. 10, Iss. 11, pp. 1320-1320
Open Access | Times Cited: 4
Screening of Gene Expression Markers for Corona Virus Disease 2019 Through Boruta_MCFS Feature Selection
Yanbao Sun, Qi Zhang, Qi Yang, et al.
Frontiers in Public Health (2022) Vol. 10
Open Access | Times Cited: 7
Explainable Machine Learning to Identify Patient-specific Biomarkers for Lung Cancer
Masrur Sobhan, Ananda Mohan Mondal
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2022), pp. 3152-3159
Open Access | Times Cited: 7
Identification of Novel microRNA Prognostic Markers Using Cascaded Wx, a Neural Network-Based Framework, in Lung Adenocarcinoma Patients
Jeong Seon Kim, Sang Hoon Chun, Sung Soo Park, et al.
Cancers (2020) Vol. 12, Iss. 7, pp. 1890-1890
Open Access | Times Cited: 10
Deep Learning for Survival Analysis: A Review
Simon Wiegrebe, Philipp Kopper, Raphael Sonabend, et al.
arXiv (Cornell University) (2023)
Open Access | Times Cited: 3
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