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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:

Predicting Long-Term Cognitive Outcome Following Breast Cancer with Pre-Treatment Resting State fMRI and Random Forest Machine Learning
Shelli R. Kesler, Arvind Rao, Douglas W. Blayney, et al.
Frontiers in Human Neuroscience (2017) Vol. 11
Open Access | Times Cited: 79

Showing 1-25 of 79 citing articles:

Machine learning in medical applications: A review of state-of-the-art methods
Mohammad Shehab, Laith Abualigah, Qusai Shambour, et al.
Computers in Biology and Medicine (2022) Vol. 145, pp. 105458-105458
Closed Access | Times Cited: 318
The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features
Zaixu Cui, Gaolang Gong
NeuroImage (2018) Vol. 178, pp. 622-637
Open Access | Times Cited: 315
Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future
Muhammad Iqbal, Zeeshan Javed, Haleema Sadia, et al.
Cancer Cell International (2021) Vol. 21, Iss. 1
Open Access | Times Cited: 212
Prevalence of cognitive impairment and change in patients with breast cancer: A systematic review of longitudinal studies
Aicha B. C. Dijkshoorn, Haike E. van Stralen, Maurits Sloots, et al.
Psycho-Oncology (2021) Vol. 30, Iss. 5, pp. 635-648
Open Access | Times Cited: 108
Prevalence of cognitive impairment following chemotherapy treatment for breast cancer: a systematic review and meta-analysis
Alexandra L. Whittaker, Rebecca P. George, Lucy O’Malley
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 105
Challenging Cognitive Load Theory: The Role of Educational Neuroscience and Artificial Intelligence in Redefining Learning Efficacy
Evgenia Gkintoni, Hera Antonopoulou, Andrew Sortwell, et al.
Brain Sciences (2025) Vol. 15, Iss. 2, pp. 203-203
Open Access | Times Cited: 2
Feasibility and psychometric quality of smartphone administered cognitive ecological momentary assessments in women with metastatic breast cancer
Ashley M. Henneghan, Emily W. Paolillo, Kathleen Van Dyk, et al.
Digital Health (2025) Vol. 11
Open Access | Times Cited: 1
Chemotherapy-induced brain changes in breast cancer survivors: evaluation with multimodality magnetic resonance imaging
Yun Feng, Xiao Dong Zhang, Gang Zheng, et al.
Brain Imaging and Behavior (2019) Vol. 13, Iss. 6, pp. 1799-1814
Closed Access | Times Cited: 59
The use of machine learning and deep learning algorithms in functional magnetic resonance imaging—A systematic review
Mamoon Rashid, Harjeet Singh, Vishal Goyal
Expert Systems (2020) Vol. 37, Iss. 6
Closed Access | Times Cited: 51
Machine Learning for Endometrial Cancer Prediction and Prognostication
Vipul Bhardwaj, Arundhiti Sharma, V. P. Snijesh, et al.
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 30
Distinct and heterogeneous trajectories of self‐perceived cognitive impairment among Asian breast cancer survivors
Terence Ng, Sreemanee Raaj Dorajoo, Yin Ting Cheung, et al.
Psycho-Oncology (2018) Vol. 27, Iss. 4, pp. 1185-1192
Closed Access | Times Cited: 54
Novel Effective Connectivity Inference Using Ultra-Group Constrained Orthogonal Forward Regression and Elastic Multilayer Perceptron Classifier for MCI Identification
Yang Li, Hao Yang, Baiying Lei, et al.
IEEE Transactions on Medical Imaging (2018) Vol. 38, Iss. 5, pp. 1227-1239
Closed Access | Times Cited: 48
The Developmental Trajectory of Cancer-Related Cognitive Impairment in Breast Cancer Patients: A Systematic Review of Longitudinal Neuroimaging Studies
Helena Sousa, Susana Almeida, João M. Bessa, et al.
Neuropsychology Review (2020) Vol. 30, Iss. 3, pp. 287-309
Open Access | Times Cited: 46
Existence of Functional Connectome Fingerprint during Infancy and Its Stability over Months
Dan Hu, Fan Wang, Han Zhang, et al.
Journal of Neuroscience (2021) Vol. 42, Iss. 3, pp. 377-389
Open Access | Times Cited: 35
Usefulness of machine learning and deep learning approaches in screening and early detection of breast cancer
Mohsen Ghorbian, ‪Saeid Ghorbian
Heliyon (2023) Vol. 9, Iss. 12, pp. e22427-e22427
Open Access | Times Cited: 14
Characterizing cancer-related cognitive impairments and impact on quality of life in women with metastatic breast cancer
Ashley M. Henneghan, Kathleen Van Dyk, Darren Haywood, et al.
Breast Cancer Research and Treatment (2024)
Closed Access | Times Cited: 5
Deep uncertainty quantification algorithms for confidence-aware hope classification of breast cancer patients based on their cognitive features
AmirReza Tajally, Javad Zarean Dowlat Abadi, Ali Bozorgi-Amiri, et al.
Applied Soft Computing (2025), pp. 112860-112860
Closed Access
Functional connectome biotypes of chemotherapy-related cognitive impairment
Shelli R. Kesler, Melissa Petersen, Vikram Rao, et al.
Journal of Cancer Survivorship (2020) Vol. 14, Iss. 4, pp. 483-493
Open Access | Times Cited: 37
A randomized control trial of meditation compared to music listening to improve cognitive function for breast cancer survivors: Feasibility and acceptability
Ashley M. Henneghan, Heather Becker, Michelle Harrison, et al.
Complementary Therapies in Clinical Practice (2020) Vol. 41, pp. 101228-101228
Open Access | Times Cited: 37
Chemotherapy-related cognitive impairment in patients with breast cancer based on MRS and DTI analysis
Taishan Tong, Heng Lu, Jian Zong, et al.
Breast Cancer (2020) Vol. 27, Iss. 5, pp. 893-902
Closed Access | Times Cited: 33
A New Fuzzy-Based Classification Method for Use in Smart/Precision Medicine
Elena Zaitseva, Vitaly Levashenko, Jan Rabčan, et al.
Bioengineering (2023) Vol. 10, Iss. 7, pp. 838-838
Open Access | Times Cited: 12
Predicting post-stroke cognitive impairment using machine learning: A prospective cohort study
Wencan Ji, Canjun Wang, Hanqing Chen, et al.
Journal of Stroke and Cerebrovascular Diseases (2023) Vol. 32, Iss. 11, pp. 107354-107354
Closed Access | Times Cited: 11
Comparison of Deep Learning and Traditional Machine Learning Models for Predicting Mild Cognitive Impairment Using Plasma Proteomic Biomarkers
Kesheng Wang, Donald Adjeroh, Wei Fang, et al.
International Journal of Molecular Sciences (2025) Vol. 26, Iss. 6, pp. 2428-2428
Open Access
Cortical Brain Age from Pre-treatment to Post-chemotherapy in Patients with Breast Cancer
Ashley M. Henneghan, Vikram Rao, Rebecca A. Harrison, et al.
Neurotoxicity Research (2020) Vol. 37, Iss. 4, pp. 788-799
Open Access | Times Cited: 31
HDAC6 inhibition reverses long-term doxorubicin-induced cognitive dysfunction by restoring microglia homeostasis and synaptic integrity
Blake McAlpin, Rajasekaran Mahalingam, Anand Kumar Singh, et al.
Theranostics (2021) Vol. 12, Iss. 2, pp. 603-619
Open Access | Times Cited: 26
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