Rita Simões

517 total citations
30 papers, 309 citations indexed

About

Rita Simões is a scholar working on Radiology, Nuclear Medicine and Imaging, Radiation and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Rita Simões has authored 30 papers receiving a total of 309 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Radiology, Nuclear Medicine and Imaging, 10 papers in Radiation and 8 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Rita Simões's work include Radiomics and Machine Learning in Medical Imaging (12 papers), Advanced Radiotherapy Techniques (10 papers) and Advances in Oncology and Radiotherapy (6 papers). Rita Simões is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (12 papers), Advanced Radiotherapy Techniques (10 papers) and Advances in Oncology and Radiotherapy (6 papers). Rita Simões collaborates with scholars based in Netherlands, United Kingdom and Australia. Rita Simões's co-authors include Uulke A. van der Heide, Cornelis H. Slump, Anne‐Marie van Cappellen van Walsum, Monique Maas, Doenja M. J. Lambregts, Geerard L. Beets, Martha Dlugaj, Bas Jasperse, Isabel Wanke and Christian Weimar and has published in prestigious journals such as International Journal of Radiation Oncology*Biology*Physics, Annals of Oncology and Physics in Medicine and Biology.

In The Last Decade

Rita Simões

23 papers receiving 306 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rita Simões Netherlands 10 223 87 60 54 53 30 309
D. Schött United States 8 302 1.4× 85 1.0× 82 1.4× 164 3.0× 17 0.3× 16 360
Haidy Nasief United States 7 297 1.3× 76 0.9× 99 1.6× 122 2.3× 13 0.2× 16 355
Xinzhi Teng Hong Kong 12 281 1.3× 98 1.1× 76 1.3× 30 0.6× 8 0.2× 41 356
Tobias Hepp Germany 12 263 1.2× 69 0.8× 86 1.4× 25 0.5× 15 0.3× 26 405
Silvia Strolin Italy 9 218 1.0× 129 1.5× 64 1.1× 81 1.5× 11 0.2× 29 362
Gisèle Pereira United States 8 257 1.2× 98 1.1× 103 1.7× 22 0.4× 6 0.1× 12 359
Yixin Hu China 8 400 1.8× 83 1.0× 75 1.3× 60 1.1× 52 1.0× 14 522
Lisa M. Kinnard United States 9 280 1.3× 168 1.9× 60 1.0× 25 0.5× 11 0.2× 14 348
Haoyu Zhong China 7 212 1.0× 45 0.5× 73 1.2× 65 1.2× 6 0.1× 21 254
Gil-Sun Hong South Korea 10 149 0.7× 49 0.6× 48 0.8× 23 0.4× 36 0.7× 33 279

Countries citing papers authored by Rita Simões

Since Specialization
Citations

This map shows the geographic impact of Rita Simões'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 Rita Simões with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rita Simões more than expected).

Fields of papers citing papers by Rita Simões

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rita Simões. 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 Rita Simões. The network helps show where Rita Simões may publish in the future.

Co-authorship network of co-authors of Rita Simões

This figure shows the co-authorship network connecting the top 25 collaborators of Rita Simões. A scholar is included among the top collaborators of Rita Simões 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 Rita Simões. Rita Simões 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.
Tyler, Justine, Helen Baines, Catharine H. Clark, et al.. (2024). 1812: Impact of radiotherapy clinical trial participation and quality assurance on head and neck practice. Radiotherapy and Oncology. 194. S2684–S2687.
2.
Keek, Simon, A. Mans, Marlies E. Nowee, et al.. (2024). 865: Clinical evaluation of organs at risk deep learning auto-segmentation for cervix brachytherapy. Radiotherapy and Oncology. 194. S333–S336. 1 indexed citations
3.
Seddon, Beatrice, Franel Le Grange, Rita Simões, et al.. (2024). The IMRiS Trial: A Phase 2 Study of Intensity Modulated Radiation Therapy in Extremity Soft Tissue Sarcoma. International Journal of Radiation Oncology*Biology*Physics. 120(4). 978–989. 3 indexed citations
4.
Duffton, Aileen, et al.. (2024). RTT advanced practice and how it can change the future of radiotherapy. Technical Innovations & Patient Support in Radiation Oncology. 30. 100245–100245. 3 indexed citations
5.
6.
Schaake, Eva E., et al.. (2023). Deep learning for segmentation of the cervical cancer gross tumor volume on magnetic resonance imaging for brachytherapy. Radiation Oncology. 18(1). 91–91. 15 indexed citations
7.
Taylor, Rachel M., et al.. (2023). Choosing the right questions – A systematic review of patient reported outcome measures used in radiotherapy and proton beam therapy. Radiotherapy and Oncology. 191. 110071–110071. 9 indexed citations
8.
9.
Al‐Mamgani, Abrahim, et al.. (2022). Strategies for tackling the class imbalance problem of oropharyngeal primary tumor segmentation on magnetic resonance imaging. Physics and Imaging in Radiation Oncology. 23. 144–149. 6 indexed citations
10.
Simões, Rita, et al.. (2021). Evaluation of delineating the target volume by radiation therapists in breast cancer patients. Technical Innovations & Patient Support in Radiation Oncology. 17. 78–81. 5 indexed citations
11.
Jasperse, Bas, et al.. (2021). Oropharyngeal primary tumor segmentation for radiotherapy planning on magnetic resonance imaging using deep learning. Physics and Imaging in Radiation Oncology. 19. 39–44. 32 indexed citations
12.
Trebeschi, Stefano, Rita Simões, Doenja M. J. Lambregts, et al.. (2020). Machine learning-based analysis of CT radiomics model for prediction of colorectal metachronous liver metastases. Abdominal Radiology. 46(1). 249–256. 65 indexed citations
13.
Simões, Rita, Elizabeth Miles, Haidong Yang, et al.. (2019). IMRiS phase II study of IMRT in limb sarcomas: Results of the pre-trial QA facility questionnaire and workshop. Radiography. 26(1). 71–75. 3 indexed citations
14.
Hatton, M., Corinne Faivre‐Finn, David Landau, et al.. (2019). Accelerated, Dose escalated, Sequential Chemoradiotherapy in Non-small-cell lung cancer (ADSCaN): a protocol for a randomised phase II study. BMJ Open. 9(1). e019903–e019903. 9 indexed citations
15.
Simões, Rita, Ghazaleh Ghobadi, Stijn W. T. P. J. Heijmink, et al.. (2019). Multiparametric MRI Tumor Probability Model for the Detection of Locally Recurrent Prostate Cancer After Radiation Therapy: Pathologic Validation and Comparison With Manual Tumor Delineations. International Journal of Radiation Oncology*Biology*Physics. 105(1). 140–148. 6 indexed citations
16.
Yang, Haidong, Patricia Díez, Y. Tsang, et al.. (2019). Provision of Organ at Risk Contouring Guidance in UK Radiotherapy Clinical Trials. Clinical Oncology. 32(2). e60–e66. 3 indexed citations
17.
Dinh, Cuong V., Iris Walraven, Stijn Heijmink, et al.. (2018). Biochemical recurrence prediction after radiotherapy for prostate cancer with T2w magnetic resonance imaging radiomic features. Physics and Imaging in Radiation Oncology. 7. 9–15. 32 indexed citations
18.
Simões, Rita, Anne‐Marie van Cappellen van Walsum, & Cornelis H. Slump. (2014). Classification and localization of early-stage Alzheimer’s disease in magnetic resonance images using a patch-based classifier ensemble. Neuroradiology. 56(9). 709–721. 16 indexed citations
19.
Simões, Rita, Christoph Mönninghoff, Martha Dlugaj, et al.. (2013). Automatic segmentation of cerebral white matter hyperintensities using only 3D FLAIR images. Magnetic Resonance Imaging. 31(7). 1182–1189. 45 indexed citations
20.
Simões, Rita & Cornelis H. Slump. (2011). Change detection and classification in brain MR images using change vector analysis. PubMed. 45. 7803–7807. 4 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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