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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.

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Showing 1-25 of 43 citing articles:

Multimodal machine learning in precision health: A scoping review
Adrienne Kline, Hanyin Wang, Yikuan Li, et al.
npj Digital Medicine (2022) Vol. 5, Iss. 1
Open Access | Times Cited: 216
SARS-Net: COVID-19 detection from chest x-rays by combining graph convolutional network and convolutional neural network
Aayush Kumar, Ayush Tripathi, Suresh Chandra Satapathy, et al.
Pattern Recognition (2021) Vol. 122, pp. 108255-108255
Open Access | Times Cited: 105
A review of deep learning-based information fusion techniques for multimodal medical image classification
Yihao Li, Mostafa El Habib Daho, Pierre-Henri Conze, et al.
Computers in Biology and Medicine (2024) Vol. 177, pp. 108635-108635
Open Access | Times Cited: 20
Quantitative Identification of Nonmuscle‐Invasive and Muscle‐Invasive Bladder Carcinomas: A Multiparametric MRI Radiomics Analysis
Xiaopan Xu, Xi Zhang, Qiang Tian, et al.
Journal of Magnetic Resonance Imaging (2018) Vol. 49, Iss. 5, pp. 1489-1498
Closed Access | Times Cited: 87
Non-small cell lung carcinoma histopathological subtype phenotyping using high-dimensional multinomial multiclass CT radiomics signature
Zahra Khodabakhshi, Shayan Mostafaei, Hossein Arabi, et al.
Computers in Biology and Medicine (2021) Vol. 136, pp. 104752-104752
Open Access | Times Cited: 76
Machine-learning-based classification of the histological subtype of non-small-cell lung cancer using MRI texture analysis
Ewelina Bębas, Marta Borowska, Marcin Derlatka, et al.
Biomedical Signal Processing and Control (2021) Vol. 66, pp. 102446-102446
Closed Access | Times Cited: 59
Multitask Learning Radiomics on Longitudinal Imaging to Predict Survival Outcomes following Risk-Adaptive Chemoradiation for Non-Small Cell Lung Cancer
Parisa Forouzannezhad, Dominic Maes, Daniel S. Hippe, et al.
Cancers (2022) Vol. 14, Iss. 5, pp. 1228-1228
Open Access | Times Cited: 28
Intratumoral and peritumoral CT-based radiomics strategy reveals distinct subtypes of non-small-cell lung cancer
Xing Tang, Haolin Huang, Peng Du, et al.
Journal of Cancer Research and Clinical Oncology (2022) Vol. 148, Iss. 9, pp. 2247-2260
Closed Access | Times Cited: 25
Radiomics feature analysis and model research for predicting histopathological subtypes of non‐small cell lung cancer on CT images: A multi‐dataset study
Fan Song, Xiao Song, Youdan Feng, et al.
Medical Physics (2023) Vol. 50, Iss. 7, pp. 4351-4365
Closed Access | Times Cited: 15
Non-Invasive Biomarkers for Early Lung Cancer Detection
Harman Saman, Afsheen Raza, Kalyani Patil, et al.
Cancers (2022) Vol. 14, Iss. 23, pp. 5782-5782
Open Access | Times Cited: 22
Beyond traditional orthopaedic data analysis: AI, multimodal models and continuous monitoring
Felix C. Oettl, Bálint Zsidai, Jacob F. Oeding, et al.
Knee Surgery Sports Traumatology Arthroscopy (2025)
Open Access
Deep learning model for distinguishing novel coronavirus from other chest related infections in X-ray images
Fareed Ahmad, Muhammad Usman Ghani Khan, Kashif Javed
Computers in Biology and Medicine (2021) Vol. 134, pp. 104401-104401
Open Access | Times Cited: 26
Reconstruction-Assisted Feature Encoding Network for Histologic Subtype Classification of Non-Small Cell Lung Cancer
Haichun Li, Qilong Song, Dongqi Gui, et al.
IEEE Journal of Biomedical and Health Informatics (2022) Vol. 26, Iss. 9, pp. 4563-4574
Closed Access | Times Cited: 16
Classification of Histological Types and Stages in Non-small Cell Lung Cancer Using Radiomic Features Based on CT Images
Jing Lin, Yunjie Yu, Xianlong Zhang, et al.
Journal of Digital Imaging (2023) Vol. 36, Iss. 3, pp. 1029-1037
Closed Access | Times Cited: 9
MRI-Based Clinical-Imaging-Radiomics Nomogram Model for Discriminating Between Benign and Malignant Solid Pulmonary Nodules or Masses
Kexin Xie, Can Cui, Xiaoqing Li, et al.
Academic Radiology (2024) Vol. 31, Iss. 10, pp. 4231-4241
Closed Access | Times Cited: 3
Dose Prediction Using a Three-Dimensional Convolutional Neural Network for Nasopharyngeal Carcinoma With Tomotherapy
Yaoying Liu, Zhaocai Chen, Jinyuan Wang, et al.
Frontiers in Oncology (2021) Vol. 11
Open Access | Times Cited: 20
Loading and release of cancer chemotherapy drugs utilizing simultaneous temperature and pH-responsive nanohybrid
Mohammad Dahri, Hossein Akbarialiabad, Ahmad Miri Jahromi, et al.
BMC Pharmacology and Toxicology (2021) Vol. 22, Iss. 1
Open Access | Times Cited: 18
Development of a Radiomics Prediction Model for Histological Type Diagnosis in Solitary Pulmonary Nodules: The Combination of CT and FDG PET
Mengmeng Yan, Weidong Wang
Frontiers in Oncology (2020) Vol. 10
Open Access | Times Cited: 18
Stage-Specific PET Radiomic Prediction Model for the Histological Subtype Classification of Non-Small-Cell Lung Cancer
Yanlei Ji, Qingtao Qiu, Jing Fu, et al.
Cancer Management and Research (2021) Vol. Volume 13, pp. 307-317
Open Access | Times Cited: 15
Elaboration of Multiparametric MRI‐Based Radiomics Signature for the Preoperative Quantitative Identification of the Histological Grade in Patients With Non‐Small‐Cell Lung Cancer
Xing Tang, Guoyan Bai, Hong Wang, et al.
Journal of Magnetic Resonance Imaging (2022) Vol. 56, Iss. 2, pp. 579-589
Closed Access | Times Cited: 9
Generating a multimodal artificial intelligence model to differentiate benign and malignant follicular neoplasms of the thyroid: A proof-of-concept study
Ann Lin, Zelong Liu, Justine Lee, et al.
Surgery (2023) Vol. 175, Iss. 1, pp. 121-127
Closed Access | Times Cited: 5
A Non-invasive Method to Diagnose Lung Adenocarcinoma
Mengmeng Yan, Weidong Wang
Frontiers in Oncology (2020) Vol. 10
Open Access | Times Cited: 13
Magnetic resonance radiomic feature performance in pulmonary nodule classification and impact of segmentation variability on radiomics
Chi Wan Koo, Timothy L. Kline, Joo Hee Yoon, et al.
British Journal of Radiology (2022) Vol. 95, Iss. 1140
Open Access | Times Cited: 8
The invasion depth measurement of bladder cancer using T2-weighted magnetic resonance imaging
Yang Liu, Haojie Zheng, Xiaopan Xu, et al.
BioMedical Engineering OnLine (2020) Vol. 19, Iss. 1
Open Access | Times Cited: 10
COVID-index: A texture-based approach to classifying lung lesions based on CT images
Vitória de Carvalho Brito, Patrick Ryan Sales dos Santos, Nonato Rodrigues de Sales Carvalho, et al.
Pattern Recognition (2021) Vol. 119, pp. 108083-108083
Open Access | Times Cited: 9
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