Hannah Thomas
About
Hannah Thomas is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology and Pulmonary and Respiratory Medicine.
According to data from OpenAlex, Hannah Thomas has authored 37 papers receiving a total of 941 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Radiology, Nuclear Medicine and Imaging, 15 papers in Oncology and 11 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Hannah Thomas's work include Radiomics and Machine Learning in Medical Imaging (15 papers), Medical Imaging Techniques and Applications (10 papers) and Lung Cancer Diagnosis and Treatment (9 papers). Hannah Thomas is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (15 papers), Medical Imaging Techniques and Applications (10 papers) and Lung Cancer Diagnosis and Treatment (9 papers). Hannah Thomas collaborates with scholars based in United States, India and United Kingdom. Hannah Thomas's co-authors include Paul Nghiem, Kristina Lachance, Shailender Bhatia, Kelly G. Paulson, John A. Thompson, Natalie Vandeven, Andreas Stang, Song Youn Park, Kelly L. Harms and Aude G. Chapuis and has published in prestigious journals such as Journal of Clinical Oncology, Scientific Reports and International Journal of Radiation Oncology*Biology*Physics.
In The Last Decade
Hannah Thomas
33 papers receiving 928 citations
Peers
Hannah Thomas
Chris Hamilton Australia
Robert G. Bourne Australia
Manisha Thakuria United States
Sylvia Pasternak Canada
Meliessa Hennessy United States
Marcis Bajars United States
Jill Ainslie Australia
Brian Schlain United States
Ahmad Kassem Germany
T. Ström United States
Citations per year, relative to Hannah Thomas Hannah Thomas (= 1×)
peers
Chris Hamilton
Countries citing papers authored by Hannah Thomas
Since
Specialization
Citations
This map shows the geographic impact of Hannah Thomas'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 Hannah Thomas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hannah Thomas more than expected).
Fields of papers citing papers by Hannah Thomas
Since
Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences
This network shows the impact of papers produced by Hannah Thomas. 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 Hannah Thomas. The network helps show where Hannah Thomas may publish in the future.
Co-authorship network of co-authors of Hannah Thomas
This figure shows the co-authorship network connecting the top 25 collaborators of Hannah Thomas. A scholar is included among the top collaborators of Hannah Thomas 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 Hannah Thomas. Hannah Thomas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
1.
Thomas, Hannah, Luis F. Gonzalez‐Cuyar, K. Mark Weaver, et al.. (2025). Clinical and Radiographic Presentation and Surgical Outcomes of T-Box Pituitary Transcription Factor (TPIT) Silent Corticotroph Pituitary Neuroendocrine Tumors: A Multi-institutional Experience and Review of the Literature. World Neurosurgery. 196. 123791–123791.
2.
Molitoris, Jason K., Ling Xiao, Lisa M. Schumaker, et al.. (2025). Graph feature selection for enhancing radiomic stability and reproducibility across multiple institutions in head and neck cancer. Scientific Reports. 15(1). 27995–27995.
3.
Chacko, Ari G., et al.. (2024). Is radiomics a useful addition to magnetic resonance imaging in the preoperative classification of PitNETs?. Acta Neurochirurgica. 166(1). 91–91.
4.
Thomas, Hannah, Ellen M. Donovan, C. South, et al.. (2023). Reproducibility in Radiomics: A Comparison of Feature Extraction Methods and Two Independent Datasets. Applied Sciences. 13(12). 7291–7291.
5.
Chandramohan, Anuradha, et al.. (2023). Teleradiology and technology innovations in radiology: status in India and its role in increasing access to primary health care. The Lancet Regional Health - Southeast Asia. 23. 100195–100195.
6.
Wee, Leonard, André Dekker, Frank Hoebers, et al.. (2023). Multi-centre radiomics for prediction of recurrence following radical radiotherapy for head and neck cancers: Consequences of feature selection, machine learning classifiers and batch-effect harmonization. Physics and Imaging in Radiation Oncology. 26. 100450–100450.
7.
Thomas, Hannah, Daniel S. Hippe, Parisa Forouzannezhad, et al.. (2022). Radiation and immune checkpoint inhibitor-mediated pneumonitis risk stratification in patients with locally advanced non-small cell lung cancer: role of functional lung radiomics?. Discover Oncology. 13(1). 85–85.
8.
Bowen, Stephen R., Daniel S. Hippe, Hannah Thomas, et al.. (2021). Prognostic Value of Early Fluorodeoxyglucose-Positron Emission Tomography Response Imaging and Peripheral Immunologic Biomarkers: Substudy of a Phase II Trial of Risk-Adaptive Chemoradiation for Unresectable Non-Small Cell Lung Cancer. Advances in Radiation Oncology. 7(2). 100857–100857.
9.
Bowen, Stephen R., et al.. (2021). Framework for Machine Learning of CT and PET Radiomics to Predict Local Failure after Radiotherapy in Locally Advanced Head and Neck Cancers. Journal of Medical Physics. 46(3). 181–188.
10.
Horn, Kevin P., Hannah Thomas, Hubert Vesselle, et al.. (2021). Reliability of Quantitative 18F-FDG PET/CT Imaging Biomarkers for Classifying Early Response to Chemoradiotherapy in Patients With Locally Advanced Non–Small Cell Lung Cancer. Clinical Nuclear Medicine. 46(11). 861–871.
11.
Akaike, Tomoko, Austin Anderson, Fatemeh Behnia, et al.. (2020). High somatostatin receptor expression and efficacy of somatostatin analogues in patients with metastatic Merkel cell carcinoma*. British Journal of Dermatology. 184(2). 319–327.
12.
Zou, Zhenwei, et al.. (2020). Scanning Beam Proton Therapy versus Photon IMRT for Stage III Lung Cancer: Comparison of Dosimetry, Toxicity, and Outcomes. Advances in Radiation Oncology. 5(3). 434–443.
13.
Tarabadkar, Erica S., Teresa Fu, Kristina Lachance, et al.. (2020). Narrow excision margins are appropriate for Merkel cell carcinoma when combined with adjuvant radiation: Analysis of 188 cases of localized disease and proposed management algorithm. Journal of the American Academy of Dermatology. 84(2). 340–347.
14.
Lewis, Christopher W., Daniel S. Hippe, Kristina Lachance, et al.. (2019). Patterns of distant metastases in 215 Merkel cell carcinoma patients: Implications for prognosis and surveillance. Cancer Medicine. 9(4). 1374–1382.
15.
Thomas, Hannah, Jing Zeng, Paul E. Kinahan, et al.. (2019). Comparison of regional lung perfusion response on longitudinal MAA SPECT/CT in lung cancer patients treated with and without functional tissue-avoidance radiation therapy. British Journal of Radiology. 92(1103). 20190174–20190174.
16.
Appelbaum, Jacob, David J. Wells, Joseph B. Hiatt, et al.. (2018). Fatal enteric plexus neuropathy after one dose of ipilimumab plus nivolumab: a case report. Journal for ImmunoTherapy of Cancer. 6(1). 82–82.
17.
Thomas, Hannah, Paul E. Kinahan, E. James Jebaseelan Samuel, & Stephen R. Bowen. (2017). Impact of tumour motion compensation and delineation methods on FDG PET ‐based dose painting plan quality for NSCLC radiation therapy. Journal of Medical Imaging and Radiation Oncology. 62(1). 81–90.
18.
Moshiri, Ata S., Ryan Doumani, Lola Yelistratova, et al.. (2016). Polyomavirus-Negative Merkel Cell Carcinoma: A More Aggressive Subtype Based on Analysis of 282 Cases Using Multimodal Tumor Virus Detection. Journal of Investigative Dermatology. 137(4). 819–827.
19.
Thomas, Hannah, et al.. (2014). Can positron emission tomography be more than a diagnostic tool? A survey on clinical practice among radiation oncologists in India. Indian Journal of Cancer. 51(2). 145–145.
20.
Thomas, Hannah, et al.. (2011). Validation of image registration and fusion of MV CBCT and planning CT for radiotherapy treatment planning. Australasian Physical & Engineering Sciences in Medicine. 34(4). 441–447.
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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