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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:

Prediction Model of Hemorrhage Transformation in Patient with Acute Ischemic Stroke Based on Multiparametric MRI Radiomics and Machine Learning
Yucong Meng, Haoran Wang, Chuanfu Wu, et al.
Brain Sciences (2022) Vol. 12, Iss. 7, pp. 858-858
Open Access | Times Cited: 26

Showing 1-25 of 26 citing articles:

Role of Brain Imaging in the Prediction of Intracerebral Hemorrhage Following Endovascular Therapy for Acute Stroke
Pierre Seners, Anke Wouters, Benjamin Maïer, et al.
Stroke (2023) Vol. 54, Iss. 8, pp. 2192-2203
Closed Access | Times Cited: 17
Predictive Value of CT Perfusion in Hemorrhagic Transformation after Acute Ischemic Stroke: A Systematic Review and Meta-Analysis
Jie Xu, Fangyu Dai, Binda Wang, et al.
Brain Sciences (2023) Vol. 13, Iss. 1, pp. 156-156
Open Access | Times Cited: 16
Application of radiomics in ischemic stroke
Jie Yang, Huabo Cai, Ning Liu, et al.
Journal of International Medical Research (2024) Vol. 52, Iss. 4
Open Access | Times Cited: 4
Artificial intelligence in ischemic stroke images: current applications and future directions
Ying Liu, Zhongjian Wen, Yiren Wang, et al.
Frontiers in Neurology (2024) Vol. 15
Open Access | Times Cited: 4
Application of radiomics in acute and severe non-neoplastic diseases: A literature review
Fang Yu, Qiannan Zhang, Junwei Yan, et al.
Journal of Critical Care (2025) Vol. 87, pp. 155027-155027
Open Access
Delta radiomics modeling based on CTP for predicting hemorrhagic transformation after intravenous thrombolysis in acute cerebral infarction: an 8-year retrospective pilot study
Xiao Wu, Yang Jin-fang, Xianqun Ji, et al.
Frontiers in Neurology (2025) Vol. 16
Open Access
Traditional and machine learning models for predicting haemorrhagic transformation in ischaemic stroke: a systematic review and meta-analysis
Yanan Wang, Z. H. Zhang, Zhimeng Zhang, et al.
Systematic Reviews (2025) Vol. 14, Iss. 1
Open Access
Optimizing acute ischemic stroke outcome prediction by integrating radiomics features of DSC-PWI and perfusion parameter maps
Yang Huihui, Yingwei Guo, Jiaxi Lu, et al.
Frontiers in Neurology (2025) Vol. 16
Open Access
Predicting hemorrhagic transformation in acute ischemic stroke: a systematic review, meta-analysis, and methodological quality assessment of CT/MRI-based deep learning and radiomics models
Mohsen Salimi, Pouria Vadipour, Amir Reza Bahadori, et al.
Emergency Radiology (2025)
Closed Access
Predicting long-term outcomes for acute ischemic stroke using multi-model MRI radiomics and clinical variables
Lai Wei, Xianpan Pan, Wei Deng, et al.
Frontiers in Medicine (2024) Vol. 11
Open Access | Times Cited: 3
Advanced Machine Learning Models for Predicting Post-Thrombolysis Hemorrhagic Transformation in Acute Ischemic Stroke Patients: A Systematic Review and Meta-Analysis
Youli Jiang, Qingshi Zhao, Ao Li, et al.
Clinical and Applied Thrombosis/Hemostasis (2024) Vol. 30
Open Access | Times Cited: 3
Artificial intelligence in emergency neuroradiology: Current applications and perspectives
Bo Gong, Farzad Khalvati, Birgit Ertl‐Wagner, et al.
Diagnostic and Interventional Imaging (2024)
Open Access | Times Cited: 3
Use of Machine Learning in Stroke Rehabilitation: A Narrative Review
Yoo Jin Choo, Min Cheol Chang
Brain & Neurorehabilitation (2022) Vol. 15, Iss. 3
Open Access | Times Cited: 15
Application and risk prediction of thrombolytic therapy in cardio-cerebrovascular diseases: a review
Kexin Zhang, Yao Jiang, Hesong Zeng, et al.
Thrombosis Journal (2023) Vol. 21, Iss. 1
Open Access | Times Cited: 6
Preoperative Molecular Subtype Classification Prediction of Ovarian Cancer Based on Multi-Parametric Magnetic Resonance Imaging Multi-Sequence Feature Fusion Network
Yijiang Du, Tingting Wang, Linhao Qu, et al.
Bioengineering (2024) Vol. 11, Iss. 5, pp. 472-472
Open Access | Times Cited: 2
Machine learning and deep learning algorithms in stroke medicine: a systematic review of hemorrhagic transformation prediction models
Mahbod Issaiy, Diana Zarei, Shahriar Kolahi, et al.
Journal of Neurology (2024) Vol. 272, Iss. 1
Open Access | Times Cited: 2
Radiomics Studies on Ischemic Stroke and Carotid Atherosclerotic Disease: A Reporting Quality Assessment
Ann‐Marie Beaudoin, J.K. Ho, Adrienne Lam, et al.
Canadian Association of Radiologists Journal (2024) Vol. 75, Iss. 3, pp. 549-557
Open Access | Times Cited: 1
Integration of graph network with kernel SVM and logistic regression for identification of biomarkers in SCA12 and its diagnosis
Snigdha Agrawal, R. K. Agrawal, S Senthil Kumaran, et al.
Cerebral Cortex (2024) Vol. 34, Iss. 4
Closed Access | Times Cited: 1
The value of radiomics-based hyperdense middle cerebral artery sign in predicting hemorrhagic transformation in acute ischemic stroke patients undergoing endovascular treatment
Chundan Gong, Yun Liu, Wei Ma, et al.
Frontiers in Neurology (2024) Vol. 15
Open Access | Times Cited: 1
Machine learning‐based radiomics in neurodegenerative and cerebrovascular disease
Meilong Shi, Feng Xiong, He Zhi, et al.
MedComm (2024) Vol. 5, Iss. 11
Open Access
An ensemble convolutional neural network model for brain stroke prediction using brain computed tomography images
Jannatul Ferdous, Rifat Shahriyar
Healthcare Analytics (2024), pp. 100368-100368
Open Access
How Can Radiomics Help the Clinical Management of Patients with Acute Ischemic Stroke?
Jacobo Porto-Álvarez, Antonio J. Mosqueira, Javier Martínez Fernández, et al.
(2023)
Open Access | Times Cited: 1
Predictors of 30-day mortality in patients with an international normalized ratio of 4.5 - 10 due to warfarin-related overanticoagulation: a retrospective cohort study
Mehmet Muzaffer İslam
Çukurova medical journal (Online)/Çukurova medical journal (2023) Vol. 48, Iss. 2, pp. 654-662
Open Access
How Can Radiomics Help the Clinical Management of Patients with Acute Ischemic Stroke?
Jacobo Porto-Álvarez, Antonio J. Mosqueira, Javier Martínez Fernández, et al.
Applied Sciences (2023) Vol. 13, Iss. 18, pp. 10061-10061
Open Access
Machine learning application in ischemic stroke diagnosis, management, and outcome prediction: a narrative review
Mi‐Yeon Eun, Eun‐Tae Jeon, Jin‐Man Jung
Journal of Medicine and Life Science (2023) Vol. 20, Iss. 4, pp. 141-157
Open Access
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