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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:

Detecting Brain Tumor using Machines Learning Techniques Based on Different Features Extracting Strategies
Lal Hussain, Sharjil Saeed, Imtiaz Ahmed Awan, et al.
Current Medical Imaging Formerly Current Medical Imaging Reviews (2019) Vol. 15, Iss. 6, pp. 595-606
Closed Access | Times Cited: 52

Showing 1-25 of 52 citing articles:

Brain tumor segmentation of MRI images: A comprehensive review on the application of artificial intelligence tools
Ramin Ranjbarzadeh, Annalina Caputo, Erfan Babaee Tırkolaee, et al.
Computers in Biology and Medicine (2022) Vol. 152, pp. 106405-106405
Closed Access | Times Cited: 150
A New Model for Brain Tumor Detection Using Ensemble Transfer Learning and Quantum Variational Classifier
Javeria Amin, Muhammad Almas Anjum, Muhammad Sharif, et al.
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-13
Open Access | Times Cited: 74
Homogeneous Adaboost Ensemble Machine Learning Algorithms with Reduced Entropy on Balanced Data
Mahesh Thyluru Ramakrishna, Vinoth Kumar Venkatesan, Ivan Izonin, et al.
Entropy (2023) Vol. 25, Iss. 2, pp. 245-245
Open Access | Times Cited: 54
Radiogenomic classification for MGMT promoter methylation status using multi-omics fused feature space for least invasive diagnosis through mpMRI scans
Shahzad Ahmad Qureshi, Lal Hussain, Usama Ibrar, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 40
Detecting prostate cancer using deep learning convolution neural network with transfer learning approach
Adeel Abbasi, Lal Hussain, Imtiaz Ahmed Awan, et al.
Cognitive Neurodynamics (2020) Vol. 14, Iss. 4, pp. 523-533
Open Access | Times Cited: 103
Prostate Cancer Detection Using Deep Learning and Traditional Techniques
Saqib Iqbal, Ghazanfar Farooq Siddiqui, Amjad Rehman, et al.
IEEE Access (2021) Vol. 9, pp. 27085-27100
Open Access | Times Cited: 80
Artificial Intelligence-Driven Diagnosis of Pancreatic Cancer
Bahrudeen Shahul Hameed, Uma Maheswari Krishnan
Cancers (2022) Vol. 14, Iss. 21, pp. 5382-5382
Open Access | Times Cited: 38
A review and comparative study of cancer detection using machine learning: SBERT and SimCSE application
Mpho Mokoatle, Vukosi Marivate, Darlington Mapiye, et al.
BMC Bioinformatics (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 28
Enhancing lung cancer detection through hybrid features and machine learning hyperparameters optimization techniques
Liangyu Li, Jing Yang, Lip Yee Por, et al.
Heliyon (2024) Vol. 10, Iss. 4, pp. e26192-e26192
Open Access | Times Cited: 9
Machine learning classification of texture features of MRI breast tumor and peri-tumor of combined pre- and early treatment predicts pathologic complete response
Lal Hussain, Pauline Huang, Tony Nguyen, et al.
BioMedical Engineering OnLine (2021) Vol. 20, Iss. 1
Open Access | Times Cited: 51
Artificial Intelligence based accurately load forecasting system to forecast short and medium-term load demands
Faisal Mehmood Butt, Lal Hussain, Anzar Mahmood, et al.
Mathematical Biosciences & Engineering (2020) Vol. 18, Iss. 1, pp. 400-425
Open Access | Times Cited: 50
The Deep Learning ResNet101 and Ensemble XGBoost Algorithm with Hyperparameters Optimization Accurately Predict the Lung Cancer
Saghir Ahmed, Basit Raza, Lal Hussain, et al.
Applied Artificial Intelligence (2023) Vol. 37, Iss. 1
Open Access | Times Cited: 18
Detecting brain tumors using deep learning convolutional neural network with transfer learning approach
Sadia Anjum, Lal Hussain, Mushtaq Ali, et al.
International Journal of Imaging Systems and Technology (2021) Vol. 32, Iss. 1, pp. 307-323
Closed Access | Times Cited: 39
Lung Cancer Prediction Using Robust Machine Learning and Image Enhancement Methods on Extracted Gray-Level Co-Occurrence Matrix Features
Lal Hussain, Hadeel Alsolai, Siwar Ben Haj Hassine, et al.
Applied Sciences (2022) Vol. 12, Iss. 13, pp. 6517-6517
Open Access | Times Cited: 23
Optimizing brain tumor classification through feature selection and hyperparameter tuning in machine learning models
Mst. Sazia Tahosin, Md. Alif Sheakh, Taminul Islam, et al.
Informatics in Medicine Unlocked (2023) Vol. 43, pp. 101414-101414
Open Access | Times Cited: 13
Detecting congestive heart failure by extracting multimodal features with synthetic minority oversampling technique (SMOTE) for imbalanced data using robust machine learning techniques
Lal Hussain, Kashif Javed Lone, Imtiaz Ahmed Awan, et al.
Waves in Random and Complex Media (2020) Vol. 32, Iss. 3, pp. 1079-1102
Closed Access | Times Cited: 28
Application of Machine Learning for Classification of Brain Tumors: A Systematic Review and Meta-Analysis
Laís Silva Santana, Jordana Borges Camargo Diniz, Luisa Mothé Glioche Gasparri, et al.
World Neurosurgery (2024) Vol. 186, pp. 204-218.e2
Closed Access | Times Cited: 3
Bayesian dynamic profiling and optimization of important ranked energy from gray level co-occurrence (GLCM) features for empirical analysis of brain MRI
Lal Hussain, Areej Malibari, Jaber S. Alzahrani, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 14
A computer-aided diagnosis system for brain tumors based on artificial intelligence algorithms
Tao Chen, Lianting Hu, Quan Lu, et al.
Frontiers in Neuroscience (2023) Vol. 17
Open Access | Times Cited: 7
Review, Limitations, and future prospects of neural network approaches for brain tumor classification
Surajit Das, Rajat Subhra Goswami
Multimedia Tools and Applications (2023) Vol. 83, Iss. 15, pp. 45799-45841
Closed Access | Times Cited: 7
Feature Ranking Importance from Multimodal Radiomic Texture Features using Machine Learning Paradigm: A Biomarker to Predict the Lung Cancer
Seong‐O Shim, Monagi H. Alkinani, Lal Hussain, et al.
Big Data Research (2022) Vol. 29, pp. 100331-100331
Closed Access | Times Cited: 11
Automated breast cancer detection by reconstruction independent component analysis (RICA) based hybrid features using machine learning paradigms
Lal Hussain, Shahzad Ahmad Qureshi, Amjad Aldweesh, et al.
Connection Science (2022) Vol. 34, Iss. 1, pp. 2784-2806
Closed Access | Times Cited: 11
Automated segmentation of brain tumour images using deep learning-based model VGG19 and ResNet 101
Sana Ali, Jitendra Agrawal
Multimedia Tools and Applications (2023) Vol. 83, Iss. 11, pp. 33351-33370
Closed Access | Times Cited: 6
Brain MR Image Classification for Glioma Tumor detection using Deep Convolutional Neural Network Features
Ghazanfar Latif, D. N. F. Awang Iskandar, Jaafar M. Alghazo, et al.
Current Medical Imaging Formerly Current Medical Imaging Reviews (2020) Vol. 17, Iss. 1, pp. 56-63
Closed Access | Times Cited: 17
Machine learning-based lungs cancer detection using reconstruction independent component analysis and sparse filter features
Lal Hussain, Majid Almaraashi, Wajid Aziz, et al.
Waves in Random and Complex Media (2021) Vol. 34, Iss. 1, pp. 226-251
Closed Access | Times Cited: 14
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