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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:

Deep learning methods for drug response prediction in cancer: Predominant and emerging trends
Alexander Partin, Thomas Brettin, Yitan Zhu, et al.
Frontiers in Medicine (2023) Vol. 10
Open Access | Times Cited: 61

Showing 26-50 of 61 citing articles:

Learning chemical sensitivity reveals mechanisms of cellular response
William Connell, Kristle Garcia, Hani Goodarzi, et al.
Communications Biology (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 1
Leveraging State-of-the-Art AI Algorithms in Personalized Oncology: From Transcriptomics to Treatment
Anwar Shams
Diagnostics (2024) Vol. 14, Iss. 19, pp. 2174-2174
Open Access | Times Cited: 1
From cancer big data to treatment: Artificial intelligence in cancer research
Mohd Danishuddin, Shawez Khan, Jong-Joo Kim
The Journal of Gene Medicine (2023) Vol. 26, Iss. 1
Closed Access | Times Cited: 4
Combination of multiple omics techniques for a personalized therapy or treatment selection
Chiara Massa, Barbara Seliger
Frontiers in Immunology (2023) Vol. 14
Open Access | Times Cited: 3
Integration of Computational Docking into Anti-Cancer Drug Response Prediction Models
Oleksandr Narykov, Yitan Zhu, Thomas Brettin, et al.
Cancers (2023) Vol. 16, Iss. 1, pp. 50-50
Open Access | Times Cited: 3
Comparison of multiple modalities for drug response prediction with learning curves using neural networks and XGBoost
Nikhil Branson, Pedro R. Cutillas, Conrad Bessant
Bioinformatics Advances (2023) Vol. 4, Iss. 1
Open Access | Times Cited: 3
Leveraging Explainable AI for Improved Understanding and Prediction of Drug Responses in IGF1R Signaling Pathways
J. Janiel, P. Selvi Rajendran
(2024), pp. 1-5
Closed Access
Understanding the Sources of Performance in Deep Learning Drug Response Prediction Models
Nikhil Branson, Pedro R. Cutillas, Conrad Besseant
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
GSDRP: Fusing Drug Sequence Features with Graph Features to Predict Drug Response
Peng Xing, Yuan Dang, Jingyun Huang, et al.
Lecture notes in computer science (2024), pp. 151-168
Closed Access
Identification of Sounds Using Deep Learning with MFCC Features Extraction
Veeramanickam M.R.M, Aniket Ingavale, Vikas Khullar, et al.
(2024), pp. 60-64
Closed Access
MGATAF: Multi-channel Graph AttentionNetwork with Adaptive Fusion forCancer-Drug Response Prediction
Dhekra Saeed, Huanlai Xing, Barakat AlBadani, et al.
Research Square (Research Square) (2024)
Open Access
Machine learning in oncological pharmacogenomics: advancing personalized chemotherapy
Çıgır Biray Avci, Bakiye Göker Bağca, Behrouz Shademan, et al.
Functional & Integrative Genomics (2024) Vol. 24, Iss. 5
Closed Access
A Multi-Modal Genomic Knowledge Distillation Framework for Drug Response Prediction
Shuang Ge, Shuqing Sun, Huan Xu, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Single-cell technology for drug discovery and development
A Zhang, Jiawei Zou, Yue Xi, et al.
Frontiers in Drug Discovery (2024) Vol. 4
Open Access
An EETR Approach for Therapeutic Response Prediction Using Gene Expression and Drug Properties
P. Selvi Rajendran, Janiel Jawahar
Lecture notes in networks and systems (2024), pp. 471-479
Closed Access
Artificial intelligence, medications, pharmacogenomics, and ethics
Susanne B. Haga
Pharmacogenomics (2024), pp. 1-12
Closed Access
Pan-Cancer Drug Sensitivity Prediction from Gene Expression using Deep Learning
Beronica A. Ocasio, Jiaming Hu, Vasileios Stathias, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Artificial intelligence: clinical applications and future advancement in gastrointestinal cancers
Abolfazl Akbari, Maryam Adabi, Mohsem Masoodi, et al.
Frontiers in Artificial Intelligence (2024) Vol. 7
Open Access
Machine Learning and Omic Data for Prediction of Health and Chronic Diseases
Mark Olenik, Handan Melike Dönertaş
Elsevier eBooks (2024)
Closed Access
Data Imbalance in Drug Response Prediction - Multi-Objective Optimization Approach in Deep Learning Setting
Oleksandr Narykov, Yitan Zhu, Thomas Brettin, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
Text-mining-based feature selection for anticancer drug response prediction
Grace C. Wu, Arvin Zaker, Amirhosein Ebrahimi, et al.
Bioinformatics Advances (2024) Vol. 4, Iss. 1
Open Access
Evaluating the Discriminative Capacity of a Random Forest Predictive Model for Deep Vein Thrombosis in Tibial Plateau Fracture Patients
Hao Liu, Fei Xing, Jiabao Jiang, et al.
Research Square (Research Square) (2024)
Open Access
Applications of AI in Biomedical Genomics and Pharmaceuticals
Mayyas Al‐Remawi, Rami A. Abdel Rahem
(2024), pp. 1-5
Closed Access
Determinants of Chromatin Organization in Aging and Cancer—Emerging Opportunities for Epigenetic Therapies and AI Technology
Rogério M. Castilho, Leonard S. Castilho, Bruna H. Palomares, et al.
Genes (2024) Vol. 15, Iss. 6, pp. 710-710
Open Access
An Ensemble Cascade Forest‐Based Framework for Multi‐Omics Drug Response and Synergy Prediction
Ruijiang Li, Binsheng Sui, Dongjin Leng, et al.
Advanced Intelligent Systems (2024)
Closed Access

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