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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:

Convolutional neural network-based PSO for lung nodule false positive reduction on CT images
Giovanni L. F. da Silva, Thales Levi Azevedo Valente, Aristófanes Corrêa Silva, et al.
Computer Methods and Programs in Biomedicine (2018) Vol. 162, pp. 109-118
Closed Access | Times Cited: 166

Showing 1-25 of 166 citing articles:

An automatic method for lung segmentation and reconstruction in chest X-ray using deep neural networks
Johnatan Carvalho Souza, João Otávio Bandeira Diniz, Jonnison Lima Ferreira, et al.
Computer Methods and Programs in Biomedicine (2019) Vol. 177, pp. 285-296
Closed Access | Times Cited: 239
Enhanced whale optimization algorithm for medical feature selection: A COVID-19 case study
Mohammad H. Nadimi-Shahraki, Hoda Zamani, Seyedali Mirjalili
Computers in Biology and Medicine (2022) Vol. 148, pp. 105858-105858
Closed Access | Times Cited: 208
Radiomics and deep learning in lung cancer
Michele Avanzo, Joseph Stancanello, G. Pirrone, et al.
Strahlentherapie und Onkologie (2020) Vol. 196, Iss. 10, pp. 879-887
Closed Access | Times Cited: 200
Lung cancer identification: a review on detection and classification
Shailesh Kumar Thakur, Dhirendra Pratap Singh, Jaytrilok Choudhary
Cancer and Metastasis Reviews (2020) Vol. 39, Iss. 3, pp. 989-998
Closed Access | Times Cited: 161
A novel IoT network intrusion detection approach based on Adaptive Particle Swarm Optimization Convolutional Neural Network
Xiu Kan, Yixuan Fan, Zhijun Fang, et al.
Information Sciences (2021) Vol. 568, pp. 147-162
Closed Access | Times Cited: 152
A survey of computer-aided diagnosis of lung nodules from CT scans using deep learning
Yu Gu, Jingqian Chi, Jiaqi Liu, et al.
Computers in Biology and Medicine (2021) Vol. 137, pp. 104806-104806
Closed Access | Times Cited: 130
COVID-19 Detection Using Deep Learning Algorithm on Chest X-ray Images
Shamima Akter, F. M. Javed Mehedi Shamrat, Sovon Chakraborty, et al.
Biology (2021) Vol. 10, Iss. 11, pp. 1174-1174
Open Access | Times Cited: 130
Application of Meta-Heuristic Algorithms for Training Neural Networks and Deep Learning Architectures: A Comprehensive Review
Mehrdad Kaveh, Mohammad Saadi Mesgari
Neural Processing Letters (2022) Vol. 55, Iss. 4, pp. 4519-4622
Open Access | Times Cited: 129
Chaotic RIME optimization algorithm with adaptive mutualism for feature selection problems
Mahmoud Abdel-Salam, Gang Hu, Emre Çelik, et al.
Computers in Biology and Medicine (2024) Vol. 179, pp. 108803-108803
Closed Access | Times Cited: 40
A neuro-heuristic approach for recognition of lung diseases from X-ray images
Qiao Ke, Jiangshe Zhang, Wei Wei, et al.
Expert Systems with Applications (2019) Vol. 126, pp. 218-232
Closed Access | Times Cited: 137
Artificial intelligence and radiomics in pulmonary nodule management: current status and future applications
Sarim Ather, Timor Kadir, Fergus Gleeson
Clinical Radiology (2019) Vol. 75, Iss. 1, pp. 13-19
Open Access | Times Cited: 133
Automatic nodule detection for lung cancer in CT images: A review
Guobin Zhang, Shan Jiang, Zhiyong Yang, et al.
Computers in Biology and Medicine (2018) Vol. 103, pp. 287-300
Closed Access | Times Cited: 119
Detection and Classification of Pulmonary Nodules Using Convolutional Neural Networks: A Survey
Patrice Monkam, Shouliang Qi, He Ma, et al.
IEEE Access (2019) Vol. 7, pp. 78075-78091
Open Access | Times Cited: 104
Automatic Pulmonary Nodule Detection Applying Deep Learning or Machine Learning Algorithms to the LIDC-IDRI Database: A Systematic Review
Lea Marie Pehrson, Michael Bachmann Nielsen, Carsten Ammitzbøl Lauridsen
Diagnostics (2019) Vol. 9, Iss. 1, pp. 29-29
Open Access | Times Cited: 102
Lungs nodule detection framework from computed tomography images using support vector machine
Sajid Ali Khan, Muhammad Nazir, Muhammad Attique Khan, et al.
Microscopy Research and Technique (2019) Vol. 82, Iss. 8, pp. 1256-1266
Closed Access | Times Cited: 93
Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19
Hanan Farhat, George E. Sakr, Rima Kilany
Machine Vision and Applications (2020) Vol. 31, Iss. 6
Open Access | Times Cited: 77
Deep Neural Architectures for Medical Image Semantic Segmentation: Review
Muhammad Zubair Khan, Mohan Kumar Gajendran, Yugyung Lee, et al.
IEEE Access (2021) Vol. 9, pp. 83002-83024
Open Access | Times Cited: 74
Lung Cancer Prediction Using Stochastic Diffusion Search (SDS) Based Feature Selection and Machine Learning Methods
S. Shanthi, N. Rajkumar
Neural Processing Letters (2020) Vol. 53, Iss. 4, pp. 2617-2630
Closed Access | Times Cited: 72
A Survey on Evolutionary Construction of Deep Neural Networks
Xun Zhou, A. K. Qin, Maoguo Gong, et al.
IEEE Transactions on Evolutionary Computation (2021) Vol. 25, Iss. 5, pp. 894-912
Open Access | Times Cited: 72
Radiomics in Lung Diseases Imaging: State-of-the-Art for Clinicians
Anne-Noëlle Frix, François Cousin, Turkey Refaee, et al.
Journal of Personalized Medicine (2021) Vol. 11, Iss. 7, pp. 602-602
Open Access | Times Cited: 69
Automatic method for classifying COVID-19 patients based on chest X-ray images, using deep features and PSO-optimized XGBoost
Domingos Dias, Luana Batista da Cruz, João Otávio Bandeira Diniz, et al.
Expert Systems with Applications (2021) Vol. 183, pp. 115452-115452
Open Access | Times Cited: 60
Wind speed estimation using novelty hybrid adaptive estimation model based on decomposition and deep learning methods (ICEEMDAN-CNN)
Cem Emeksiz, Mustafa Tan
Energy (2022) Vol. 249, pp. 123785-123785
Closed Access | Times Cited: 44
Reproducible Machine Learning Methods for Lung Cancer Detection Using Computed Tomography Images: Algorithm Development and Validation
Kun‐Hsing Yu, Michael T. Lee, Ming-Hsuan Yen, et al.
Journal of Medical Internet Research (2020) Vol. 22, Iss. 8, pp. e16709-e16709
Open Access | Times Cited: 65
Evaluating the performance of a deep learning‐based computer‐aided diagnosis (DL‐CAD) system for detecting and characterizing lung nodules: Comparison with the performance of double reading by radiologists
Li Li, Zhou Liu, Hua Huang, et al.
Thoracic Cancer (2018) Vol. 10, Iss. 2, pp. 183-192
Open Access | Times Cited: 63
NCTN Assessment on Current Applications of Radiomics in Oncology
Ke Nie, Hania Al‐Hallaq, X. Allen Li, et al.
International Journal of Radiation Oncology*Biology*Physics (2019) Vol. 104, Iss. 2, pp. 302-315
Open Access | Times Cited: 55
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