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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:

Machine Learning analysis of high-grade serous ovarian cancer proteomic dataset reveals novel candidate biomarkers
Federica Farinella, Mario Merone, Luca Bacco, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 14

Showing 14 citing articles:

Artificial intelligence assists precision medicine in cancer treatment
Jinzhuang Liao, M Kellis, Yu Gan, et al.
Frontiers in Oncology (2023) Vol. 12
Open Access | Times Cited: 98
Robust biomarker screening from gene expression data by stable machine learning-recursive feature elimination methods
Lingyu Li, Wai‐Ki Ching, Zhi-Ping Liu
Computational Biology and Chemistry (2022) Vol. 100, pp. 107747-107747
Closed Access | Times Cited: 34
Machine learning use in early ovarian cancer detection
Emmanuel Kokori, Nicholas Aderinto, Gbolahan Olatunji, et al.
Deleted Journal (2025) Vol. 2, Iss. 1
Open Access
Advances and challenges in thyroid cancer: The interplay of genetic modulators, targeted therapies, and AI-driven approaches
Srinjan Bhattacharya, Rahul Kumar Mahato, Satwinder Singh, et al.
Life Sciences (2023) Vol. 332, pp. 122110-122110
Open Access | Times Cited: 10
Long Short-Term Memory-Deep Belief Network-Based Gene Expression Data Analysis for Prostate Cancer Detection and Classification
Bijaya Kumar Sethi, Debabrata Singh, Saroja Kumar Rout, et al.
IEEE Access (2023) Vol. 12, pp. 1508-1524
Open Access | Times Cited: 8
Ovarian Cancer Detection Based on Elman Recurrent Neural Network
Hameed R. Farhan, Muayad Kod, Arwa Mohammed Taqi, et al.
Periodica Polytechnica Electrical Engineering and Computer Science (2024) Vol. 68, Iss. 2, pp. 202-212
Open Access | Times Cited: 2
BBOX1 mediates metabolic reprogramming driven by hypoxia and participates in the malignant progress of high-grade serous ovarian cancer
Jiazhen Huang, Ying Tang, Yibing Li, et al.
Biochimica et Biophysica Acta (BBA) - Molecular Cell Research (2024) Vol. 1871, Iss. 8, pp. 119830-119830
Closed Access | Times Cited: 2
Artificial intelligence in cancer pathology: Challenge to meet increasing demands of precision medicine
Boan Lai, Jianjiang Fu, Qingxin Zhang, et al.
International Journal of Oncology (2023) Vol. 63, Iss. 3
Closed Access | Times Cited: 4
Machine-learning diagnostic models for ovarian tumors
Yuwei Sun, Bin Wen
Heliyon (2024) Vol. 10, Iss. 19, pp. e36994-e36994
Open Access | Times Cited: 1
Artificial Intelligence in Ovarian Digital Pathology
Katie E. Allen, Pratik Adusumilli, Jack Breen, et al.
Springer eBooks (2023), pp. 731-749
Closed Access | Times Cited: 2
AUTOSurv: Interpretable Deep Learning Framework for Cancer Survival Analysis Incorporating Clinical and Multi-omics Data
Lindong Jiang, Chao Xu, Yuntong Bai, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 1
CARSINOS DETECTION USING DEEP LEARNING IN FEMININE GONADS
Malavika Ap
International Research Journal of Modernization in Engineering Technology and Science (2023)
Open Access
Oncology in the modern era: Artificial Intelligence is reshaping cancer diagnosis, prognosis and treatment
Mahda Delshad, Mohammad Amin Omrani, Atieh Pourbagheri‐Sigaroodi, et al.
Iranian Journal of Blood and Cancer (2023) Vol. 15, Iss. 3, pp. 13-41
Open Access
A Diagnostic Model of Ovarian Neoplasms by Machine Learning
Yuwei Sun, Bin Wen
(2023)
Closed Access
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