OpenAlex Citation Counts

OpenAlex Citations Logo

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 Artificial Intelligence (XAI) in Pain Research: Understanding the Role of Electrodermal Activity for Automated Pain Recognition
Philip Gouverneur, Frédéric Li, Kimiaki Shirahama, et al.
Sensors (2023) Vol. 23, Iss. 4, pp. 1959-1959
Open Access | Times Cited: 13

Showing 13 citing articles:

Explainable machine learning models based on multimodal time-series data for the early detection of Parkinson’s disease
Muhammad Junaid, Sajid Ali, Fatma Eid, et al.
Computer Methods and Programs in Biomedicine (2023) Vol. 234, pp. 107495-107495
Closed Access | Times Cited: 46

Current methods in explainable artificial intelligence and future prospects for integrative physiology
Bettina Finzel
Pflügers Archiv - European Journal of Physiology (2025)
Open Access | Times Cited: 1

Electrodermal activity in pain assessment and its clinical applications
Youngsun Kong, Ki H. Chon
Applied Physics Reviews (2024) Vol. 11, Iss. 3
Closed Access | Times Cited: 6

Unlocking the black box: an in-depth review on interpretability, explainability, and reliability in deep learning
Emrullah Şahin, Naciye Nur Arslan, Durmuş Özdemir
Neural Computing and Applications (2024)
Closed Access | Times Cited: 6

Artificial intelligence in chronic pain management: A mini review
Athira Ramesh, Amarjeet Kumar, Ajeet Kumar
Journal of Indira Gandhi Institute Of Medical Sciences (2025) Vol. 11, Iss. 1, pp. 20-25
Open Access

Explaining Pain: On the Impact of Physiological Signals in Pain Prediction
Bruna Alves, Susana Brás, Raquel Sebastião
Lecture notes in computer science (2025), pp. 70-87
Closed Access

A Review of Voice-Based Pain Detection in Adults Using Artificial Intelligence
Sahar Borna, Clifton R. Haider, Karla C. Maita, et al.
Bioengineering (2023) Vol. 10, Iss. 4, pp. 500-500
Open Access | Times Cited: 8

Ensemble Learning-Based Pain Intensity Identification Model Using Facial Expressions
Abdul Rahaman Wahab Sait, Ashit Kumar Dutta
Deleted Journal (2024) Vol. 3, Iss. 3
Open Access | Times Cited: 2

Transforming personalized chronic pain management with artificial intelligence: A commentary on the current landscape and future directions
Stefano Casarin, Nele A. Haelterman, Keren Machol
Experimental Neurology (2024) Vol. 382, pp. 114980-114980
Open Access | Times Cited: 2

Recent Applications of Explainable AI (XAI): A Systematic Literature Review
Mirka Saarela, Vili Podgorelec
Applied Sciences (2024) Vol. 14, Iss. 19, pp. 8884-8884
Open Access | Times Cited: 2

Objective Measurement of Subjective Pain Perception with Autonomic Body Reactions in Healthy Subjects and Chronic Back Pain Patients: An Experimental Heat Pain Study
Luisa Luebke, Philip Gouverneur, Tibor M. Szikszay, et al.
Sensors (2023) Vol. 23, Iss. 19, pp. 8231-8231
Open Access | Times Cited: 4

An Experimental and Clinical Physiological Signal Dataset for Automated Pain Recognition
Philip Gouverneur, Aleksandra Badura, Frédéric Li, et al.
Scientific Data (2024) Vol. 11, Iss. 1
Open Access | Times Cited: 1

Exploring the Applications of Explainability in Wearable Data Analytics: Systematic Literature Review
Yasmin Abdelaal, Michaël Aupetit, Abdelkader Baggag, et al.
Journal of Medical Internet Research (2024) Vol. 26, pp. e53863-e53863
Open Access | Times Cited: 1

Exploring the Applications of Explainability in Wearable Data Analytics: Systematic Literature Review (Preprint)
Yasmin Abdelaal, Michaël Aupetit, Abdelkader Baggag, et al.
(2023)
Closed Access

Page 1

Scroll to top