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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:

A Cascade Deep Forest Model for Breast Cancer Subtype Classification Using Multi-Omics Data
Ala’a El-Nabawy, Nahla A. Belal, Nashwa El-Bendary
Mathematics (2021) Vol. 9, Iss. 13, pp. 1574-1574
Open Access | Times Cited: 16

Showing 16 citing articles:

A Linear Discriminant Analysis and Classification Model for Breast Cancer Diagnosis
Marion O. Adebiyi, Micheal Olaolu Arowolo, Moses Damilola Mshelia, et al.
Applied Sciences (2022) Vol. 12, Iss. 22, pp. 11455-11455
Open Access | Times Cited: 46
A Comprehensive Review of Artificial Intelligence Approaches in Omics Data Processing: Evaluating Progress and Challenges
Ali Mahmoud Ali, Mazin Abed Mohammed
International Journal of Mathematics Statistics and Computer Science (2023) Vol. 2, pp. 114-167
Open Access | Times Cited: 35
Revolutionizing Breast Cancer Diagnosis: A Concatenated Precision through Transfer Learning in Histopathological Data Analysis
Dhayanithi Jaganathan, Sathiyabhama Balasubramaniam, Vidhushavarshini Sureshkumar, et al.
Diagnostics (2024) Vol. 14, Iss. 4, pp. 422-422
Open Access | Times Cited: 6
An Optimized Deep-Forest Algorithm Using a Modified Differential Evolution Optimization Algorithm: A Case of Host-Pathogen Protein-Protein Interaction Prediction.
Jerry Emmanuel, Itunuoluwa Isewon, Jelili Oyelade
Computational and Structural Biotechnology Journal (2025)
Open Access
Advanced segmentation method for integrating multi-omics data for early cancer detection
S Sangeetha, Sandeep Kumar Mathivanan, M. Azath, et al.
Egyptian Informatics Journal (2025) Vol. 29, pp. 100624-100624
Closed Access
Identifying Antitubercular Peptides via Deep Forest Architecture with Effective Feature Representation
Lantian Yao, Jiahui Guan, Wenshuo Li, et al.
Analytical Chemistry (2024)
Closed Access | Times Cited: 2
MODILM: towards better complex diseases classification using a novel multi-omics data integration learning model
Yating Zhong, Yuzhong Peng, Yanmei Lin, et al.
BMC Medical Informatics and Decision Making (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 6
DCE-DForest: A Deep Forest Model for the Prediction of Anticancer Drug Combination Effects
Wei Zhang, Ziyun Xue, Zhong Li, et al.
Computational and Mathematical Methods in Medicine (2022) Vol. 2022, pp. 1-5
Open Access | Times Cited: 10
Characterization of spleen and lymph node cell types via CITE-seq and machine learning methods
Hao Li, Deling Wang, Xianchao Zhou, et al.
Frontiers in Molecular Neuroscience (2022) Vol. 15
Open Access | Times Cited: 5
Omics data classification using constitutive artificial neural network optimized with single candidate optimizer
S Madhan, Anbarasan Kalaiselvan
Network Computation in Neural Systems (2024), pp. 1-25
Closed Access
Adap-BDCM: Adaptive Bilinear Dynamic Cascade Model for Classification Tasks on CNV Datasets
Liancheng Jiang, Liye Jia, Yizhen Wang, et al.
Interdisciplinary Sciences Computational Life Sciences (2024) Vol. 16, Iss. 4, pp. 1019-1037
Closed Access
CAEM-GBDT: a cancer subtype identifying method using multi-omics data and convolutional autoencoder network
Jiquan Shen, Xuanhui Guo, Hanwen Bai, et al.
Frontiers in Bioinformatics (2024) Vol. 4
Open Access
EpiBrCan-Lite: A Lightweight Deep Learning model for Breast Cancer Subtype Classification using Epigenomic Data
Punam Bedi, Surbhi Rani, Bhavna Gupta, et al.
Computer Methods and Programs in Biomedicine (2024) Vol. 260, pp. 108553-108553
Closed Access
Special Issue “Statistical Data Modeling and Machine Learning with Applications”
Snezhana Gocheva-Ilieva
Mathematics (2021) Vol. 9, Iss. 23, pp. 2997-2997
Open Access | Times Cited: 1
Advancing Breast Cancer Diagnosis with Machine Learning: Exploring Data Balancing, Feature Selection, and Bayesian Optimization
Abd Allah Aouragh, Mohamed Bahaj
(2023), pp. 01-06
Closed Access
Analisis Bibliometrik Penelitian Pohon Keputusan untuk Prediksi Kanker Payudara
Suhartono Suhartono, Totok Chamidy, Syahiduz Zaman
Journal of Documentation and Information Science (2023) Vol. 7, Iss. 2
Open Access
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