Sarah Jo Stephens

588 total citations
29 papers, 387 citations indexed

About

Sarah Jo Stephens is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Radiation. According to data from OpenAlex, Sarah Jo Stephens has authored 29 papers receiving a total of 387 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Radiology, Nuclear Medicine and Imaging, 7 papers in Pulmonary and Respiratory Medicine and 5 papers in Radiation. Recurrent topics in Sarah Jo Stephens's work include Hepatocellular Carcinoma Treatment and Prognosis (5 papers), Advanced Radiotherapy Techniques (5 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). Sarah Jo Stephens is often cited by papers focused on Hepatocellular Carcinoma Treatment and Prognosis (5 papers), Advanced Radiotherapy Techniques (5 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). Sarah Jo Stephens collaborates with scholars based in United States, France and Italy. Sarah Jo Stephens's co-authors include Manisha Palta, Christopher G. Willett, Brian G. Czito, Ethan B. Ludmir, Joseph K. Salama, Michael J. Moravan, R París, Yvonne M. Mowery, Joaquı́n M. Espinosa and Ryan E. Henry and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and Cancer.

In The Last Decade

Sarah Jo Stephens

27 papers receiving 386 citations

Peers

Sarah Jo Stephens
Maren Knödler Germany
Megan Eguchi United States
Fabio Marazzi Italy
Markus Glatzer Switzerland
Toufic Eid Lebanon
Lindsey Mitrani United States
Holly Hartman United States
Richard Khor Australia
D A Hall United States
Marley Boyd United States
Maren Knödler Germany
Sarah Jo Stephens
Citations per year, relative to Sarah Jo Stephens Sarah Jo Stephens (= 1×) peers Maren Knödler

Countries citing papers authored by Sarah Jo Stephens

Since Specialization
Citations

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

Fields of papers citing papers by Sarah Jo Stephens

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sarah Jo Stephens. 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 Sarah Jo Stephens. The network helps show where Sarah Jo Stephens may publish in the future.

Co-authorship network of co-authors of Sarah Jo Stephens

This figure shows the co-authorship network connecting the top 25 collaborators of Sarah Jo Stephens. A scholar is included among the top collaborators of Sarah Jo Stephens 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 Sarah Jo Stephens. Sarah Jo Stephens 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.
Ayala-Peacock, D.N., et al.. (2024). Retrospective assessment of HDR brachytherapy dose calculation methods in locally advanced cervical cancer patients: AcurosBV vs. AAPM TG43 formalism. Journal of Applied Clinical Medical Physics. 26(1). e14549–e14549. 1 indexed citations
2.
Li, Xuelong, et al.. (2024). A Reinforcement Learning Approach to Automate Breast Radiation Therapy Treatment Planning Using Electronic Compensation (ECOMP). International Journal of Radiation Oncology*Biology*Physics. 120(2). S63–S63.
3.
4.
Eisenstein, Eric L., Samantha M. Thomas, Neville Eclov, et al.. (2024). Health Care Cost Reductions with Machine Learning–Directed Evaluations during Radiation Therapy — An Economic Analysis of a Randomized Controlled Study. NEJM AI. 1(4). 5 indexed citations
5.
Ayala-Peacock, D.N., et al.. (2023). A novel multi‐modality imaging phantom for validating interstitial needle guidance for high dose rate gynecological brachytherapy. Journal of Applied Clinical Medical Physics. 24(10). e14075–e14075. 2 indexed citations
6.
Hong, Julian C., Neville Eclov, Sarah Jo Stephens, et al.. (2023). Healthcare provider evaluation of machine learning-directed care: reactions to deployment on a randomised controlled study. BMJ Health & Care Informatics. 30(1). e100674–e100674. 3 indexed citations
7.
Leng, Jim, David Carpenter, Junzo Chino, et al.. (2023). LMAP-08 MULTI-INSTITUTIONAL CLINICAL OUTCOMES FOLLOWING STEREOTACTIC RADIOSURGERY FOR BRAIN METASTASES FROM GYNECOLOGIC MALIGNANCIES. Neuro-Oncology Advances. 5(Supplement_3). iii10–iii11. 1 indexed citations
8.
Stephens, Sarah Jo, et al.. (2022). Role of stereotactic body radiotherapy in gynecologic radiation oncology. International Journal of Gynecological Cancer. 32(3). 372–379. 8 indexed citations
9.
Hong, Julian C., Neville Eclov, Sarah Jo Stephens, Yvonne M. Mowery, & Manisha Palta. (2022). Implementation of machine learning in the clinic: challenges and lessons in prospective deployment from the System for High Intensity EvaLuation During Radiation Therapy (SHIELD-RT) randomized controlled study. BMC Bioinformatics. 23(S12). 408–408. 8 indexed citations
10.
Thomas, Samantha M., Neville Eclov, Sarah Jo Stephens, et al.. (2021). Machine Learning Algorithm Prospectively Predicts Survival for High-Risk Patients Undergoing Radiotherapy: A Survival Analysis of SHIELD-RT. International Journal of Radiation Oncology*Biology*Physics. 111(3). S113–S113. 1 indexed citations
11.
Lloyd, Maxwell R., Sarah Jo Stephens, Julian C. Hong, et al.. (2021). The impact of COVID-19 on breast cancer stage at diagnosis.. Journal of Clinical Oncology. 39(15_suppl). 528–528. 7 indexed citations
12.
Stephens, Sarah Jo, et al.. (2020). Evaluating for disparities in place of death for head and neck cancer patients in the United States utilizing the CDC WONDER database. Oral Oncology. 102. 104555–104555. 16 indexed citations
13.
Hong, Julian C., Neville Eclov, Samantha Thomas, et al.. (2020). System for High-Intensity Evaluation During Radiation Therapy (SHIELD-RT): A Prospective Randomized Study of Machine Learning–Directed Clinical Evaluations During Radiation and Chemoradiation. Journal of Clinical Oncology. 38(31). 3652–3661. 59 indexed citations
14.
Chino, Fumiko, Sarah Jo Stephens, Steve S. Choi, et al.. (2018). The role of external beam radiotherapy in the treatment of hepatocellular cancer. Cancer. 124(17). 3476–3489. 23 indexed citations
15.
Stephens, Sarah Jo, Michael J. Moravan, & Joseph K. Salama. (2018). Managing Patients With Oligometastatic Non–Small-Cell Lung Cancer. Journal of Oncology Practice. 14(1). 23–31. 36 indexed citations
16.
Ali, Moiez, Erin Kaltenbrun, Grace R. Anderson, et al.. (2017). Codon bias imposes a targetable limitation on KRAS-driven therapeutic resistance. Nature Communications. 8(1). 15617–15617. 33 indexed citations
17.
Stephens, Sarah Jo, Samantha M. Thomas, David A. Rizzieri, et al.. (2016). Myeloablative conditioning with total body irradiation for AML: Balancing survival and pulmonary toxicity. Advances in Radiation Oncology. 1(4). 272–280. 7 indexed citations
18.
Meyerhoff, Robert, Sarah Jo Stephens, Terry Singhapricha, et al.. (2015). Long-Term Outcomes of Lobectomy for Non-Small Cell Lung Cancer After Definitive Radiation Treatment. The Annals of Thoracic Surgery. 99(6). 1914–1920. 34 indexed citations
19.
París, R, et al.. (2008). Multiple p53-independent gene silencing mechanisms define the cellular response to p53 activation. Cell Cycle. 7(15). 2427–2433. 52 indexed citations
20.
Dixon, A.K., C. E. L. Freer, Lars Häll, et al.. (1988). MR Imaging using a Rampable System. Journal of Computer Assisted Tomography. 12(5). 903–904. 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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