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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:

Machine Learning for Predicting Outcomes in Trauma
Nehemiah T. Liu, José Salinas
Shock (2017) Vol. 48, Iss. 5, pp. 504-510
Closed Access | Times Cited: 104

Showing 1-25 of 104 citing articles:

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury
Benjamin Gravesteijn, Daan Nieboer, Ari Ercole, et al.
Journal of Clinical Epidemiology (2020) Vol. 122, pp. 95-107
Open Access | Times Cited: 160
A Machine Learning Prediction Model of Respiratory Failure Within 48 Hours of Patient Admission for COVID-19: Model Development and Validation
Siavash Bolourani, Max Brenner, Ping Wang, et al.
Journal of Medical Internet Research (2021) Vol. 23, Iss. 2, pp. e24246-e24246
Open Access | Times Cited: 99
Comparison between logistic regression and machine learning algorithms on survival prediction of traumatic brain injuries
Jinzhou Feng, Yu Wang, Peng Jin, et al.
Journal of Critical Care (2019) Vol. 54, pp. 110-116
Closed Access | Times Cited: 98
The use of machine learning techniques in trauma-related disorders: a systematic review
Luís Francisco Ramos-Lima, Vitória Waikamp, Thyago Antonelli-Salgado, et al.
Journal of Psychiatric Research (2019) Vol. 121, pp. 159-172
Closed Access | Times Cited: 82
A review on utilizing machine learning technology in the fields of electronic emergency triage and patient priority systems in telemedicine: Coherent taxonomy, motivations, open research challenges and recommendations for intelligent future work
Omar Hussein Salman, Zahraa K. Taha, Muntadher Alsabah, et al.
Computer Methods and Programs in Biomedicine (2021) Vol. 209, pp. 106357-106357
Closed Access | Times Cited: 67
Artificial intelligence and machine learning for hemorrhagic trauma care
Henry T. Peng, M. Musaab Siddiqui, Shawn G. Rhind, et al.
Military Medical Research (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 24
The recent two decades of traumatic brain injury: a bibliometric analysis and systematic review
Ziyin Ye, Zhi Li, Shiyu Zhong, et al.
International Journal of Surgery (2024)
Open Access | Times Cited: 9
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: 31
Hospital mortality prediction in traumatic injuries patients: comparing different SMOTE-based machine learning algorithms
Roghayyeh Hassanzadeh, Maryam Farhadian, Hassan Rafieemehr
BMC Medical Research Methodology (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 22
Risks in the Management of Polytrauma Patients: Clinical Insights
Karthikeyan P. Iyengar, Aakaash Venkatesan, Vijay Kumar Jain, et al.
Orthopedic Research and Reviews (2023) Vol. Volume 15, pp. 27-38
Open Access | Times Cited: 17
Artificial intelligence in neurosciences: A clinician's perspective
Krishnan Ganapathy, Shabbir Syed-Abdul, Aldilas Achmad Nursetyo
Neurology India (2018) Vol. 66, Iss. 4, pp. 934-934
Closed Access | Times Cited: 50
Artificial intelligence: A tool for sports trauma prediction
Georgios Kakavas, Nikos Malliaropoulos, Ricard Pruna, et al.
Injury (2019) Vol. 51, pp. S63-S65
Closed Access | Times Cited: 45
Feasibility of Machine Learning and Logistic Regression Algorithms to Predict Outcome in Orthopaedic Trauma Surgery
Jacobien H. F. Oosterhoff, Benjamin Gravesteijn, Aditya V. Karhade, et al.
Journal of Bone and Joint Surgery (2021) Vol. 104, Iss. 6, pp. 544-551
Open Access | Times Cited: 40
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
Exploring the effectiveness of artificial intelligence, machine learning and deep learning in trauma triage: A systematic review and meta-analysis
Oluwasemilore Adebayo, Zunira Areeba Bhuiyan, Zubair Ahmed
Digital Health (2023) Vol. 9
Open Access | Times Cited: 14
Application of machine learning techniques in the diagnostic approach of PTSD using MRI neuroimaging data: A systematic review
Yingjie Jia, Bo Yang, Yi‐Hsin Yang, et al.
Heliyon (2024) Vol. 10, Iss. 7, pp. e28559-e28559
Open Access | Times Cited: 5
Use of machine-learning algorithms to determine features of systolic blood pressure variability that predict poor outcomes in hypertensive patients
Ronilda Lacson, Bowen Baker, Harini Suresh, et al.
Clinical Kidney Journal (2018) Vol. 12, Iss. 2, pp. 206-212
Open Access | Times Cited: 46
Using machine learning to predict early readmission following esophagectomy
Siavash Bolourani, Mohammad A. Tayebi, Li Diao, et al.
Journal of Thoracic and Cardiovascular Surgery (2020) Vol. 161, Iss. 6, pp. 1926-1939.e8
Open Access | Times Cited: 36
An evidential reasoning rule based feature selection for improving trauma outcome prediction
Fatima Almaghrabi, Dong‐Ling Xu, Jianbo Yang
Applied Soft Computing (2021) Vol. 103, pp. 107112-107112
Closed Access | Times Cited: 30
Artificial intelligence and neurological health
Arinjay Jain, Shipra Dwivedi, Neeru Jain, et al.
Methods in microbiology (2025)
Closed Access
Ten Machine Learning Models for Predicting Preoperative and Postoperative Coagulopathy in Patients With Trauma: Multicenter Cohort Study
Xiaojuan Xiong, Fu Hong, Bo Xu, et al.
Journal of Medical Internet Research (2025) Vol. 27, pp. e66612-e66612
Open Access
Machine learning-based prediction of mortality in pediatric trauma patients
Alex Deleon, Anish Murala, Isabelle Decker, et al.
Frontiers in Pediatrics (2025) Vol. 13
Open Access
Using machine learning tools to predict outcomes for emergency department intensive care unit patients
Qiangrong Zhai, Zi Lin, Hongxia Ge, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 31
Is Artificial Intelligence Better Than Human Clinicians in Predicting Patient Outcomes?
Joon Lee
Journal of Medical Internet Research (2020) Vol. 22, Iss. 8, pp. e19918-e19918
Open Access | Times Cited: 28
Machine Learning Can be Used to Predict Function but Not Pain After Surgery for Thumb Carpometacarpal Osteoarthritis
Nina L. Loos, Lisa Hoogendam, J. Sebastiaan Souer, et al.
Clinical Orthopaedics and Related Research (2022) Vol. 480, Iss. 7, pp. 1271-1284
Open Access | Times Cited: 18
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