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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:

Predicting Outcome of Traumatic Brain Injury: Is Machine Learning the Best Way?
Roberta Bruschetta, Gennaro Tartarisco, Lucia Francesca Lucca, et al.
Biomedicines (2022) Vol. 10, Iss. 3, pp. 686-686
Open Access | Times Cited: 23

Showing 23 citing articles:

Application of Machine Learning Models for Early Detection and Accurate Classification of Type 2 Diabetes
Orlando Iparraguirre-Villanueva, Karina Espinola-Linares, Rosalynn Ornella Flores-Castañeda, et al.
Diagnostics (2023) Vol. 13, Iss. 14, pp. 2383-2383
Open Access | Times Cited: 38
Prognosis prediction in traumatic brain injury patients using machine learning algorithms
Hosseinali Khalili, Maziyar Rismani, Mohammad Ali Nematollahi, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 33
Predicting Outcome in Patients with Brain Injury: Differences between Machine Learning versus Conventional Statistics
Antonio Cerasa, Gennaro Tartarisco, Roberta Bruschetta, et al.
Biomedicines (2022) Vol. 10, Iss. 9, pp. 2267-2267
Open Access | Times Cited: 30
Long-term survival prediction in patients with acute brain lesions using ensemble machine learning algorithms: a cohort study with combined national health insurance service and its self-run hospital database
Dougho Park, Su Yun Lee, Suntak Jin, et al.
Journal Of Big Data (2025) Vol. 12, Iss. 1
Open Access
Is artificial intelligence superior to traditional regression methods in predicting prognosis of adult traumatic brain injury?
Matheus Fernando Manzolli Ballestero, Leandro Cândido de Souza, Alexandre L. M. Levada, et al.
Neurosurgical Review (2025) Vol. 48, Iss. 1
Closed Access
Artificial Intelligence and Machine Learning Applications in Critically Ill Brain Injured Patients
Jeffrey R. Vitt, Shraddha Mainali
Seminars in Neurology (2024) Vol. 44, Iss. 03, pp. 342-356
Closed Access | Times Cited: 4
Comparison of Machine Learning Models in Predicting Mental Health Sequelae Following Concussion in Youth
Jin Peng, Jiayuan Chen, Changchang Yin, et al.
medRxiv (Cold Spring Harbor Laboratory) (2025)
Open Access
Machine Learning in Neuroimaging of Traumatic Brain Injury: Current Landscape, Research Gaps, and Future Directions
Kevin Pierre, Jordan Turetsky, Abheek Raviprasad, et al.
Trauma Care (2024) Vol. 4, Iss. 1, pp. 31-43
Open Access | Times Cited: 3
Usefulness of Artificial Intelligence in Traumatic Brain Injury: A Bibliometric Analysis and Mini-review
Maria José Uparela-Reyes, Lina María Villegas-Trujillo, Jorge Cespedes, et al.
World Neurosurgery (2024) Vol. 188, pp. 83-92
Open Access | Times Cited: 3
Applicability of artificial intelligence in neuropsychological rehabilitation of patients with brain injury
Veselin Medenica, Lidija Ivanović, Neda Milošević
Applied Neuropsychology Adult (2024), pp. 1-28
Closed Access | Times Cited: 3
Use of Support Vector Machines Approach via ComBat Harmonized Diffusion Tensor Imaging for the Diagnosis and Prognosis of Mild Traumatic Brain Injury: A CENTER-TBI Study
Maíra Siqueira Pinto, Stefan Winzeck, Evgenios Kornaropoulos, et al.
Journal of Neurotrauma (2023) Vol. 40, Iss. 13-14, pp. 1317-1338
Open Access | Times Cited: 8
Machine learning prediction models for in-hospital postoperative functional outcome after moderate-to-severe traumatic brain injury
Anan Yin, Feng Zhang, Yalong He, et al.
European Journal of Trauma and Emergency Surgery (2024) Vol. 50, Iss. 4, pp. 1219-1228
Closed Access | Times Cited: 2
Machine learning‐based prediction of clinical outcomes after traumatic brain injury: Hidden information of early physiological time series
Ruifeng Ding, Mengqiu Deng, Huawei Wei, et al.
CNS Neuroscience & Therapeutics (2024) Vol. 30, Iss. 7
Open Access | Times Cited: 2
Machine learning models for predicting in-hospital outcomes after non-surgical treatment among patients with moderate-to-severe traumatic brain injury
Anan Yin, Yalong He, Feng Zhang, et al.
Journal of Clinical Neuroscience (2024) Vol. 120, pp. 36-41
Closed Access | Times Cited: 1
Machine learning algorithms for improved prediction of in-hospital outcomes after moderate-to-severe traumatic brain injury: a Chinese retrospective cohort study
Zan Zhang, Shengju Wang, Kun Chen, et al.
Acta Neurochirurgica (2023) Vol. 165, Iss. 8, pp. 2237-2247
Closed Access | Times Cited: 3
Machine Learning Approach for the Prediction of In-Hospital Mortality in Traumatic Brain Injury Using Bio-Clinical Markers at Presentation to the Emergency Department
Ahammed Mekkodathil, Ayman El‐Menyar, Mashhood Naduvilekandy, et al.
Diagnostics (2023) Vol. 13, Iss. 15, pp. 2605-2605
Open Access | Times Cited: 3
Traumatic Brain Injury Rehabilitation Outcome Prediction Using Machine Learning Methods
Nitin Nikamanth Appiah Balaji, Cynthia L. Beaulieu, Jennifer Bogner, et al.
Archives of Rehabilitation Research and Clinical Translation (2023) Vol. 5, Iss. 4, pp. 100295-100295
Open Access | Times Cited: 3
Automatic Lesion Analysis for Increased Efficiency in Outcome Prediction of Traumatic Brain Injury
Margherita Rosnati, Eyal Soreq, Miguel Monteiro, et al.
Lecture notes in computer science (2022), pp. 135-146
Closed Access | Times Cited: 3
Supervised Learning Algorithm Comparison in Discharge Status Prediction of Trauma Patients: Empirical Evaluation
Zahra Kohzadi, Ali Mohammad Nickfarjam, Zeinab Kohzadi, et al.
Journal of Biomedical Physics and Engineering (2024) Vol. online
Open Access
A data augmentation method for war trauma based on the regression model and deep neural networks
Jibin Yin, G. R. Liao, Yi Zhang, et al.
Soft Computing (2024)
Closed Access
Predicting return to work after traumatic brain injury using machine learning and administrative data
Helena Van Deynse, Wilfried Cools, Viktor-Jan De Deken, et al.
International Journal of Medical Informatics (2023) Vol. 178, pp. 105201-105201
Open Access | Times Cited: 1
Integrating unsupervised and supervised learning techniques to predict traumatic brain injury: A population-based study
Suvd Zulbayar, Tatyana Mollayeva, Angela Colantonio, et al.
Intelligence-Based Medicine (2023) Vol. 8, pp. 100118-100118
Open Access | Times Cited: 1
Machine learning and network analysis for diagnosis and prediction in disorders of consciousness
Ajit Narayanan, Wendy L. Magee, Richard J. Siegert
BMC Medical Informatics and Decision Making (2023) Vol. 23, Iss. 1
Open Access
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