Simukayi Mutasa

1.7k total citations
38 papers, 1.2k citations indexed

About

Simukayi Mutasa is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Simukayi Mutasa has authored 38 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Radiology, Nuclear Medicine and Imaging, 19 papers in Artificial Intelligence and 8 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Simukayi Mutasa's work include Radiomics and Machine Learning in Medical Imaging (18 papers), AI in cancer detection (18 papers) and Artificial Intelligence in Healthcare and Education (8 papers). Simukayi Mutasa is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (18 papers), AI in cancer detection (18 papers) and Artificial Intelligence in Healthcare and Education (8 papers). Simukayi Mutasa collaborates with scholars based in United States. Simukayi Mutasa's co-authors include Richard Ha, Peter Chang, Sachin Jambawalikar, Shawn Sun, Michael Z. Liu, Jenika Karcich, Eduardo Pascual Van Sant, Carrie Ruzal‐Shapiro, Rama S. Ayyala and Ralph Wynn and has published in prestigious journals such as PLoS ONE, Stroke and American Journal of Roentgenology.

In The Last Decade

Simukayi Mutasa

38 papers receiving 1.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Simukayi Mutasa United States 20 723 484 209 169 148 38 1.2k
Tomoyuki Fujioka Japan 22 874 1.2× 540 1.1× 300 1.4× 198 1.2× 161 1.1× 94 1.5k
Keno K. Bressem Germany 26 785 1.1× 427 0.9× 534 2.6× 229 1.4× 224 1.5× 109 1.8k
Anuj Pareek United States 12 634 0.9× 639 1.3× 320 1.5× 159 0.9× 161 1.1× 23 1.5k
J. Titano United States 14 746 1.0× 518 1.1× 394 1.9× 176 1.0× 294 2.0× 31 1.7k
Alireza Mehrtash United States 16 1.2k 1.7× 482 1.0× 260 1.2× 328 1.9× 443 3.0× 32 1.8k
Phillip M. Cheng United States 17 990 1.4× 379 0.8× 283 1.4× 402 2.4× 308 2.1× 34 1.7k
Bryan He United States 14 672 0.9× 348 0.7× 222 1.1× 178 1.1× 145 1.0× 31 1.6k
Jaron Chong Canada 20 649 0.9× 209 0.4× 293 1.4× 176 1.0× 136 0.9× 52 1.2k
Christoph Kern Germany 14 983 1.4× 449 0.9× 494 2.4× 158 0.9× 120 0.8× 36 1.8k
Thomas Sanford United States 19 583 0.8× 420 0.9× 103 0.5× 182 1.1× 390 2.6× 63 1.4k

Countries citing papers authored by Simukayi Mutasa

Since Specialization
Citations

This map shows the geographic impact of Simukayi Mutasa's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Simukayi Mutasa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simukayi Mutasa more than expected).

Fields of papers citing papers by Simukayi Mutasa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Simukayi Mutasa. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Simukayi Mutasa. The network helps show where Simukayi Mutasa may publish in the future.

Co-authorship network of co-authors of Simukayi Mutasa

This figure shows the co-authorship network connecting the top 25 collaborators of Simukayi Mutasa. A scholar is included among the top collaborators of Simukayi Mutasa based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Simukayi Mutasa. Simukayi Mutasa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Jambawalikar, Sachin, et al.. (2024). Deep Learning-Assisted Diffusion Tensor Imaging for Evaluation of the Physis and Metaphysis. Journal of Imaging Informatics in Medicine. 37(2). 756–765. 1 indexed citations
2.
Venkatesh, K., et al.. (2024). Gradient-Based Saliency Maps Are Not Trustworthy Visual Explanations of Automated AI Musculoskeletal Diagnoses. Journal of Imaging Informatics in Medicine. 37(5). 2490–2499. 1 indexed citations
3.
Ro, Vicky, Simukayi Mutasa, Mary Beth Terry, et al.. (2023). Breast cancer risk prediction combining a convolutional neural network-based mammographic evaluation with clinical factors. Breast Cancer Research and Treatment. 200(2). 237–245. 16 indexed citations
4.
Mutasa, Simukayi & Paul H. Yi. (2021). Clinical Artificial Intelligence Applications. Radiologic Clinics of North America. 59(6). 1013–1026. 6 indexed citations
5.
Mutasa, Simukayi & Paul H. Yi. (2021). Deciphering musculoskeletal artificial intelligence for clinical applications: how do I get started?. Skeletal Radiology. 51(2). 271–278. 4 indexed citations
6.
Mutasa, Simukayi, Shawn Sun, & Richard Ha. (2021). Understanding artificial intelligence based radiology studies: CNN architecture. Clinical Imaging. 80. 72–76. 25 indexed citations
7.
Pan, Ian, Grayson L. Baird, Simukayi Mutasa, et al.. (2020). Rethinking Greulich and Pyle: A Deep Learning Approach to Pediatric Bone Age Assessment Using Pediatric Trauma Hand Radiographs. Radiology Artificial Intelligence. 2(4). e190198–e190198. 26 indexed citations
8.
Shaish, Hiram, Firas S. Ahmed, David J. Lederer, et al.. (2020). Deep Learning of Computed Tomography Virtual Wedge Resection for Prediction of Histologic Usual Interstitial Pneumonitis. Annals of the American Thoracic Society. 18(1). 51–59. 30 indexed citations
9.
Mutasa, Simukayi, et al.. (2020). Advanced Deep Learning Techniques Applied to Automated Femoral Neck Fracture Detection and Classification. Journal of Digital Imaging. 33(5). 1209–1217. 76 indexed citations
10.
Mutasa, Simukayi, et al.. (2020). Dynamic Changes of Convolutional Neural Network-based Mammographic Breast Cancer Risk Score Among Women Undergoing Chemoprevention Treatment. Clinical Breast Cancer. 21(4). e312–e318. 9 indexed citations
11.
Chow, Daniel, Justin Glavis‐Bloom, Jennifer E. Soun, et al.. (2020). Development and external validation of a prognostic tool for COVID-19 critical disease. PLoS ONE. 15(12). e0242953–e0242953. 13 indexed citations
12.
Mutasa, Simukayi, Shawn Sun, & Richard Ha. (2020). Understanding artificial intelligence based radiology studies: What is overfitting?. Clinical Imaging. 65. 96–99. 160 indexed citations
13.
Mutasa, Simukayi, et al.. (2020). Prospective Analysis Using a Novel CNN Algorithm to Distinguish Atypical Ductal Hyperplasia From Ductal Carcinoma in Situ in Breast. Clinical Breast Cancer. 20(6). e757–e760. 6 indexed citations
14.
Liu, Michael Z., R. Vanguri, Simukayi Mutasa, et al.. (2020). Channel width optimized neural networks for liver and vessel segmentation in liver iron quantification. Computers in Biology and Medicine. 122. 103798–103798. 17 indexed citations
15.
Mutasa, Simukayi, Peter Chang, Eduardo Pascual Van Sant, et al.. (2019). Potential Role of Convolutional Neural Network Based Algorithm in Patient Selection for DCIS Observation Trials Using a Mammogram Dataset. Academic Radiology. 27(6). 774–779. 11 indexed citations
16.
Ha, Richard, Peter Chang, Jenika Karcich, et al.. (2018). Predicting Post Neoadjuvant Axillary Response Using a Novel Convolutional Neural Network Algorithm. Annals of Surgical Oncology. 25(10). 3037–3043. 26 indexed citations
17.
Ha, Richard, Peter Chang, Jenika Karcich, et al.. (2018). Axillary Lymph Node Evaluation Utilizing Convolutional Neural Networks Using MRI Dataset. Journal of Digital Imaging. 31(6). 851–856. 52 indexed citations
18.
Ha, Richard, Peter Chang, Eralda Mema, et al.. (2018). Fully Automated Convolutional Neural Network Method for Quantification of Breast MRI Fibroglandular Tissue and Background Parenchymal Enhancement. Journal of Digital Imaging. 32(1). 141–147. 36 indexed citations
19.
Ha, Richard, Peter Chang, Jenika Karcich, et al.. (2018). Convolutional Neural Network Based Breast Cancer Risk Stratification Using a Mammographic Dataset. Academic Radiology. 26(4). 544–549. 44 indexed citations
20.
Mutasa, Simukayi. (2017). Images in COPD: Bullous Emphysema with Mycetoma. Chronic Obstructive Pulmonary Diseases Journal of the COPD Foundation. 4(2). 164–167. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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