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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:

Decay Replay Mining to Predict Next Process Events
Julian Theis, Houshang Darabi
IEEE Access (2019) Vol. 7, pp. 119787-119803
Open Access | Times Cited: 47

Showing 1-25 of 47 citing articles:

A systematic literature review on state-of-the-art deep learning methods for process prediction
Dominic Alexander Neu, Johannes Lahann, Peter Fettke
Artificial Intelligence Review (2021) Vol. 55, Iss. 2, pp. 801-827
Open Access | Times Cited: 116
Improving the In-Hospital Mortality Prediction of Diabetes ICU Patients Using a Process Mining/Deep Learning Architecture
Julian Theis, William Galanter, Andrew D. Boyd, et al.
IEEE Journal of Biomedical and Health Informatics (2021) Vol. 26, Iss. 1, pp. 388-399
Open Access | Times Cited: 71
Deep Learning for Predictive Business Process Monitoring: Review and Benchmark
Efrén Rama-Maneiro, Juan C. Vidal, Manuel Lama
IEEE Transactions on Services Computing (2021), pp. 1-1
Open Access | Times Cited: 65
Explainable Artificial Intelligence for Process Mining: A General Overview and Application of a Novel Local Explanation Approach for Predictive Process Monitoring
Nijat Mehdiyev, Peter Fettke
Studies in computational intelligence (2021), pp. 1-28
Closed Access | Times Cited: 57
Machine learning in business process management: A systematic literature review
Sven Weinzierl, Sandra Zilker, Sebastian Dunzer, et al.
Expert Systems with Applications (2024) Vol. 253, pp. 124181-124181
Open Access | Times Cited: 9
A Multi-View Deep Learning Approach for Predictive Business Process Monitoring
Vincenzo Pasquadibisceglie, Annalisa Appice, Giovanna Castellano, et al.
IEEE Transactions on Services Computing (2021) Vol. 15, Iss. 4, pp. 2382-2395
Closed Access | Times Cited: 43
Building interpretable models for business process prediction using shared and specialised attention mechanisms
Bemali Wickramanayake, Zhipeng He, Chun Ouyang, et al.
Knowledge-Based Systems (2022) Vol. 248, pp. 108773-108773
Open Access | Times Cited: 30
An Interrogative Survey of Explainable AI in Manufacturing
Zoë Alexander, Duen Horng Chau, Christopher Saldaña
IEEE Transactions on Industrial Informatics (2024) Vol. 20, Iss. 5, pp. 7069-7081
Closed Access | Times Cited: 7
Embedding Graph Convolutional Networks in Recurrent Neural Networks for Predictive Monitoring
Efrén Rama-Maneiro, Juan C. Vidal, Manuel Lama
IEEE Transactions on Knowledge and Data Engineering (2023) Vol. 36, Iss. 1, pp. 137-151
Open Access | Times Cited: 11
Incremental Predictive Process Monitoring: The Next Activity Case
Stephen Pauwels, Toon Calders
Lecture notes in computer science (2021), pp. 123-140
Closed Access | Times Cited: 22
A Deep Adversarial Model for Suffix and Remaining Time Prediction of Event Sequences
Farbod Taymouri, Marcello La Rosa, Sarah M. Erfani
Society for Industrial and Applied Mathematics eBooks (2021), pp. 522-530
Open Access | Times Cited: 18
A review of AI and machine learning contribution in business process management (process enhancement and process improvement approaches)
Mostafa Abbasi, Rahnuma Islam Nishat, Corey Bond, et al.
Business Process Management Journal (2024)
Closed Access | Times Cited: 2
Predictive End-to-End Enterprise Process Network Monitoring
Felix Oberdorf, Myriam Schaschek, Sven Weinzierl, et al.
Business & Information Systems Engineering (2022) Vol. 65, Iss. 1, pp. 49-64
Open Access | Times Cited: 10
An empirical comparison of deep-neural-network architectures for next activity prediction using context-enriched process event logs
Sven Weinzierl, Sandra Zilker, Jens Brunk, et al.
arXiv (Cornell University) (2020)
Open Access | Times Cited: 13
Model-Agnostic Event Log Augmentation for Predictive Process Monitoring
Martin Käppel, Stefan Jablonski
Lecture notes in computer science (2023), pp. 381-397
Closed Access | Times Cited: 4
MTLFormer: Multi-Task Learning Guided Transformer Network for Business Process Prediction
Jiaojiao Wang, Jiawei Huang, Xiaoyu Ma, et al.
IEEE Access (2023) Vol. 11, pp. 76722-76738
Open Access | Times Cited: 4
VERONA: A python library for benchmarking deep learning in business process monitoring
Pedro Gamallo-Fernandez, Efrén Rama-Maneiro, Juan C. Vidal, et al.
SoftwareX (2024) Vol. 26, pp. 101734-101734
Open Access | Times Cited: 1
Process Mining/ Deep Learning Model to Predict Mortality in Coronary Artery Disease Patients
Negin Ashrafi, Armin Abdollahi, Greg Placencia, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
Local Post-Hoc Explanations for Predictive Process Monitoring in Manufacturing
Nijat Mehdiyev, Peter Fettke
arXiv (Cornell University) (2020)
Open Access | Times Cited: 10
Adversarial System Variant Approximation to Quantify Process Model Generalization
Julian Theis, Houshang Darabi
IEEE Access (2020) Vol. 8, pp. 194410-194427
Open Access | Times Cited: 9
Process Mining Discovery Techniques for Software Architecture Lightweight Evaluation Framework
Mahdi Sahlabadi, Ravie Chandren Muniyandi, Zarina Shukur, et al.
Computers, materials & continua/Computers, materials & continua (Print) (2022) Vol. 74, Iss. 3, pp. 5777-5797
Open Access | Times Cited: 6
Deep Learning for Predictive Business Process Monitoring: Review and Benchmark.
Efrén Rama-Maneiro, Juan C. Vidal, Manuel Lama
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 7
Explainable Business Process Remaining Time Prediction Using Reachability Graph
Rui Cao, Qingtian Zeng, Weijian Ni, et al.
Chinese Journal of Electronics (2023) Vol. 32, Iss. 3, pp. 625-639
Open Access | Times Cited: 2
Decision-Making Based on Predictive Process Monitoring of Patient Treatment Processes: A Case Study of Emergency Patients
Agaraoli Aravazhi, Berit Irene Helgheim, Petter Aadahl
Advances in Operations Research (2023) Vol. 2023, pp. 1-10
Open Access | Times Cited: 2
Dynamic Resource Allocation for Executable BPMN Processes Leveraging Predictive Analytics
Ylìès Falcone, Gwen Salaün, Ahang Zuo
(2024), pp. 689-700
Open Access
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