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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:

Construction of the XGBoost model for early lung cancer prediction based on metabolic indices
Xiuliang Guan, Yue Du, Rufei Ma, et al.
BMC Medical Informatics and Decision Making (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 29

Showing 1-25 of 29 citing articles:

Liquid biopsy techniques and lung cancer: diagnosis, monitoring and evaluation
Fei Ren, Qian Fei, Kun Qiu, et al.
Journal of Experimental & Clinical Cancer Research (2024) Vol. 43, Iss. 1
Open Access | Times Cited: 37
Machine learning-based models for the prediction of breast cancer recurrence risk
Duo Zuo, Lexin Yang, Yu Jin, et al.
BMC Medical Informatics and Decision Making (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 36
Integrating Omics Data and AI for Cancer Diagnosis and Prognosis
Y. Ozaki, P M Broughton, Hamed Abdollahi, et al.
Cancers (2024) Vol. 16, Iss. 13, pp. 2448-2448
Open Access | Times Cited: 12
MetDIT: Transforming and Analyzing Clinical Metabolomics Data with Convolutional Neural Networks
Yuyang Sha, Weiyu Meng, Gang Luo, et al.
Analytical Chemistry (2024)
Closed Access | Times Cited: 7
Integrating Omics Data and AI for Cancer Diagnosis and Prognosis: A Systematic Review
Yousaku Ozaki, P M Broughton, Hamed Abdollahi, et al.
(2024)
Open Access | Times Cited: 5
Classification of NSCLC subtypes using lung microbiome from resected tissue based on machine learning methods
Prof. Manish K. Kashyap, Kalbhavi Vadhi Raj, Jyoti Sharma, et al.
npj Systems Biology and Applications (2025) Vol. 11, Iss. 1
Open Access
Artificial Intelligence in Temporomandibular Joint Disorders: An Umbrella Review
Vini Mehta, Snehasish Tripathy, Toufiq Noor, et al.
Clinical and Experimental Dental Research (2025) Vol. 11, Iss. 1
Open Access
Exploring Primary and Interaction Effects of Minor Physical Anomalies: Development and Validation of Prediction Models Using Explainable Machine Learning Algorithms for Early-Onset Schizophrenia
Chih-Wei Lin, Jin‐Jia Lin, Huai‐Hsuan Tseng, et al.
Schizophrenia Bulletin (2025)
Closed Access
Multiclass Classification of Lung Cancer with SVM and XGBoost with 20+ Features
Zahereel Ishwar Abdul Khalib, Nur Hafizah Ghazali, SC Wong
Studies in computational intelligence (2025), pp. 317-327
Closed Access
Breast cancer prediction modeling based on SHAP interpretability analysis and XGBoost algorithm
Xiuliang Guan, Jiaxue Cui, Lan Bai, et al.
Research Square (Research Square) (2025)
Closed Access
A potential XGBoost Diagnostic Score for Staphylococcus aureus bloodstream infection
Junhong Shi, Lan Chen, Xinru Yuan, et al.
Frontiers in Immunology (2025) Vol. 16
Open Access
Risk prediction and effect evaluation of complicated appendicitis based on XGBoost modeling
Sunmeng Chen, Jianfu Xia, Beibei Xu, et al.
BMC Gastroenterology (2025) Vol. 25, Iss. 1
Open Access
Enhancing CNN-Based Network Intrusion Detection through Hyperparameter Optimization
Ali Bou Nassif, Nour Ayman Abujabal, Aya Al-Chikh Omar
Intelligent Systems with Applications (2025), pp. 200528-200528
Open Access
Alcohol extract of Rubia yunnanensis: Metabolic alterations and preventive effects against OGD/R‑induced oxidative damage in HT22 cells
Jianghao Cheng, Gaoyizhou Li, Liping Yang, et al.
Biomedical Reports (2024) Vol. 20, Iss. 5
Open Access | Times Cited: 3
Exploring metabolic anomalies in COVID-19 and post-COVID-19: a machine learning approach with explainable artificial intelligence
Juan José Oropeza-Valdez, Cristian Padrón-Manrique, Aarón Vázquez-Jiménez, et al.
Frontiers in Molecular Biosciences (2024) Vol. 11
Open Access | Times Cited: 2
Risk of intraoperative hemorrhage during cesarean scar ectopic pregnancy surgery: development and validation of an interpretable machine learning prediction model
Chen Xin-li, Huan Zhang, Dong Guo, et al.
EClinicalMedicine (2024) Vol. 78, pp. 102969-102969
Open Access | Times Cited: 2
Machine learning reveals CAT gene as a novel potential diagnostic and prognostic biomarker in non-small cell lung cancer
Yi Tian, Wen-Ya Zhao, Yiru Liu, et al.
Discover Oncology (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 2
Machine Learning Techniques to Predict Timeliness of Care among Lung Cancer Patients
Arul Earnest, Getayeneh Antehunegn Tesema, Rob G. Stirling
Healthcare (2023) Vol. 11, Iss. 20, pp. 2756-2756
Open Access | Times Cited: 6
Machine Learning Model of ResNet50-Ensemble Voting for Malignant–Benign Small Pulmonary Nodule Classification on Computed Tomography Images
Weiming Li, Siqi Yu, Runhuang Yang, et al.
Cancers (2023) Vol. 15, Iss. 22, pp. 5417-5417
Open Access | Times Cited: 5
Identification of crosstalk genes relating to ECM‐receptor interaction genes in MASH and DN using bioinformatics and machine learning
Chao Chen, Yuxi He, Ying Ni, et al.
Journal of Cellular and Molecular Medicine (2024) Vol. 28, Iss. 6
Open Access | Times Cited: 1
[Research Progress on Tumor Metabolic Biomarkers in Liquid Biopsy of Lung Cancer].
Shishi Zou, Ning Li, Tianyu Zhang, et al.
PubMed (2024) Vol. 27, Iss. 2, pp. 126-132
Closed Access | Times Cited: 1
Causal Forest Machine Learning Analysis of Parkinson’s Disease in Resting-State Functional Magnetic Resonance Imaging
Gabriel Solana-Lavalle, Michael D. Cusimano, Thomas Steeves, et al.
Tomography (2024) Vol. 10, Iss. 6, pp. 894-911
Open Access | Times Cited: 1
Non-Specific Elevated Serum Free Fatty Acids in Lung Cancer Patients: Nutritional or Pathological?
Yelin Shao, Sicong Wang, Xiaohang Xu, et al.
Nutrients (2024) Vol. 16, Iss. 17, pp. 2884-2884
Open Access | Times Cited: 1
Machine learning and explainable artificial intelligence to predict pathologic stage in men with localized prostate cancer
Hemal Semwal, Colton Ladbury, Ali Sabbagh, et al.
The Prostate (2024)
Open Access | Times Cited: 1
Lung Cancer Disease Prediction using Hybrid Subtractive Clustering Method
Banibrata Paul, Mahmood Hussain Mir, Stalin Murugan, et al.
(2024), pp. 1-6
Closed Access
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