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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:

Explainable machine-learning predictions for the prevention of hypoxaemia during surgery
Scott Lundberg, Bala G. Nair, Monica S. Vavilala, et al.
Nature Biomedical Engineering (2018) Vol. 2, Iss. 10, pp. 749-760
Open Access | Times Cited: 1486

Showing 1-25 of 1486 citing articles:

From local explanations to global understanding with explainable AI for trees
Scott Lundberg, Gabriel Erion, Hugh Chen, et al.
Nature Machine Intelligence (2020) Vol. 2, Iss. 1, pp. 56-67
Open Access | Times Cited: 5145
High-performance medicine: the convergence of human and artificial intelligence
Eric J. Topol
Nature Medicine (2018) Vol. 25, Iss. 1, pp. 44-56
Closed Access | Times Cited: 4765
Artificial intelligence in healthcare
Kun‐Hsing Yu, Andrew L. Beam, Isaac S. Kohane
Nature Biomedical Engineering (2018) Vol. 2, Iss. 10, pp. 719-731
Closed Access | Times Cited: 2026
Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography
Kang Zhang, Xiaohong Liu, Jun Shen, et al.
Cell (2020) Vol. 181, Iss. 6, pp. 1423-1433.e11
Open Access | Times Cited: 828
Scientific discovery in the age of artificial intelligence
Hanchen Wang, Tianfan Fu, Yuanqi Du, et al.
Nature (2023) Vol. 620, Iss. 7972, pp. 47-60
Closed Access | Times Cited: 691
Automated machine learning: Review of the state-of-the-art and opportunities for healthcare
Jonathan Waring, Charlotta Lindvall, Renato Umeton
Artificial Intelligence in Medicine (2020) Vol. 104, pp. 101822-101822
Open Access | Times Cited: 664
Deep learning in cancer diagnosis, prognosis and treatment selection
Khoa Tran, Olga Kondrashova, Andrew P. Bradley, et al.
Genome Medicine (2021) Vol. 13, Iss. 1
Open Access | Times Cited: 576
Explainable Deep Learning Models in Medical Image Analysis
Amitojdeep Singh, Sourya Sengupta, Vasudevan Lakshminarayanan
Journal of Imaging (2020) Vol. 6, Iss. 6, pp. 52-52
Open Access | Times Cited: 532
Machine learning-based prediction of COVID-19 diagnosis based on symptoms
Yazeed Zoabi, Shira Deri-Rozov, Noam Shomron
npj Digital Medicine (2021) Vol. 4, Iss. 1
Open Access | Times Cited: 468
Interpretability of machine learning‐based prediction models in healthcare
Gregor Štiglic, Primož Kocbek, Nino Fijačko, et al.
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (2020) Vol. 10, Iss. 5
Open Access | Times Cited: 373
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance
Gagan Bansal, Tongshuang Wu, Joyce Zhou, et al.
(2021), pp. 1-16
Open Access | Times Cited: 363
Interpretation of Compound Activity Predictions from Complex Machine Learning Models Using Local Approximations and Shapley Values
Raquel Rodríguez-Pérez, Jürgen Bajorath
Journal of Medicinal Chemistry (2019) Vol. 63, Iss. 16, pp. 8761-8777
Open Access | Times Cited: 319
Beyond Accuracy: The Role of Mental Models in Human-AI Team Performance
Gagan Bansal, Besmira Nushi, Ece Kamar, et al.
Proceedings of the AAAI Conference on Human Computation and Crowdsourcing (2019) Vol. 7, pp. 2-11
Open Access | Times Cited: 314
Restructured society and environment: A review on potential technological strategies to control the COVID-19 pandemic
Rajvikram Madurai Elavarasan, Rishi Pugazhendhi
The Science of The Total Environment (2020) Vol. 725, pp. 138858-138858
Open Access | Times Cited: 308
Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities
Marinka Žitnik, Francis Nguyen, Bo Wang, et al.
Information Fusion (2018) Vol. 50, pp. 71-91
Open Access | Times Cited: 286
Development and Validation of the Quick COVID-19 Severity Index: A Prognostic Tool for Early Clinical Decompensation
Adrian D. Haimovich, Neal G. Ravindra, Stoytcho Stoytchev, et al.
Annals of Emergency Medicine (2020) Vol. 76, Iss. 4, pp. 442-453
Open Access | Times Cited: 282
Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records
Hans‐Christian Thorsen‐Meyer, Annelaura Bach Nielsen, Anna Pors Nielsen, et al.
The Lancet Digital Health (2020) Vol. 2, Iss. 4, pp. e179-e191
Open Access | Times Cited: 257
Prediction of gestational diabetes based on nationwide electronic health records
Nitzan Shalom Artzi, Smadar Shilo, Eran Hadar, et al.
Nature Medicine (2020) Vol. 26, Iss. 1, pp. 71-76
Closed Access | Times Cited: 233
An Explainable Machine Learning Framework for Intrusion Detection Systems
Maonan Wang, Kangfeng Zheng, Yanqing Yang, et al.
IEEE Access (2020) Vol. 8, pp. 73127-73141
Open Access | Times Cited: 232
A multilayer multimodal detection and prediction model based on explainable artificial intelligence for Alzheimer’s disease
Shaker El–Sappagh, José M. Alonso, S. M. Riazul Islam, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 231
70 years of machine learning in geoscience in review
Jesper Dramsch
Advances in geophysics (2020), pp. 1-55
Open Access | Times Cited: 222
Explainable machine learning can outperform Cox regression predictions and provide insights in breast cancer survival
Arturo Moncada‐Torres, Marissa C. van Maaren, Mathijs P. Hendriks, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 221
Metabolomic profiles predict individual multidisease outcomes
Thore Buergel, Jakob Steinfeldt, Greg Ruyoga, et al.
Nature Medicine (2022) Vol. 28, Iss. 11, pp. 2309-2320
Open Access | Times Cited: 221
Surgical data science – from concepts toward clinical translation
Lena Maier‐Hein, Matthias Eisenmann, Duygu Sarıkaya, et al.
Medical Image Analysis (2021) Vol. 76, pp. 102306-102306
Open Access | Times Cited: 220
From explanations to feature selection: assessing SHAP values as feature selection mechanism
Wilson E. Marcílio-Jr, Danilo Medeiros Eler
(2020), pp. 340-347
Closed Access | Times Cited: 209
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