David J. Carlson

6.0k total citations · 2 hit papers
91 papers, 4.4k citations indexed

About

David J. Carlson is a scholar working on Pulmonary and Respiratory Medicine, Radiation and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, David J. Carlson has authored 91 papers receiving a total of 4.4k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Pulmonary and Respiratory Medicine, 36 papers in Radiation and 31 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in David J. Carlson's work include Radiation Therapy and Dosimetry (33 papers), Advanced Radiotherapy Techniques (32 papers) and Breast Cancer Treatment Studies (21 papers). David J. Carlson is often cited by papers focused on Radiation Therapy and Dosimetry (33 papers), Advanced Radiotherapy Techniques (32 papers) and Breast Cancer Treatment Studies (21 papers). David J. Carlson collaborates with scholars based in United States, Germany and Italy. David J. Carlson's co-authors include J. Martin Brown, Robert D. Stewart, David J. Brenner, Kelly M. McMasters, Todd M. Tuttle, R. Dirk Noyes, Peter S. Turk, Chelsea Brown, Patricia B. Cerrito and Sandra L. Wong and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Annals of Internal Medicine.

In The Last Decade

David J. Carlson

85 papers receiving 4.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The Tumor Radiobiology of SRS and SBRT: Are More Than the 5 Rs Involved?

2014 389 citations David J. Carlson et al. International Journal of Radiation Oncology*Biology*Physics profile →
Report of the AAPM TG‐256 on the relative biological effectiveness of proton beams in radiation therapy

2019 212 citations Harald Paganetti, Eleanor A. Blakely et al. Medical Physics profile →

Peers

David J. Carlson

PRM

RADIA

PFM

SURGE

Coen Hurkmans Netherlands

Marianne Aznar United Kingdom

Jürgen Dunst Germany

Inga S. Grills United States

Barbara Silver United States

Thomas A. DiPetrillo United States

Michael MacManus Australia

Mathias Bressel Australia

Leonard R. Prosnitz United States

Thomas F. DeLaney United States

Coen Hurkmans Netherlands

David J. Carlson

3.0k ×1.5

PRM

1.4k ×0.7

3.4k ×2.2

RADIA

539 ×0.4

PFM

881 ×0.7

SURGE

Citations per year, relative to David J. Carlson David J. Carlson (= 1×) peers Coen Hurkmans

Countries citing papers authored by David J. Carlson

Since Specialization

Citations

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

Fields of papers citing papers by David J. Carlson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David J. Carlson. 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 David J. Carlson. The network helps show where David J. Carlson may publish in the future.

Co-authorship network of co-authors of David J. Carlson

This figure shows the co-authorship network connecting the top 25 collaborators of David J. Carlson. A scholar is included among the top collaborators of David J. Carlson 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 David J. Carlson. David J. Carlson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Wang, Yuenan, et al.. (2025). Deep learning with attention modules and residual transformations improves hepatocellular carcinoma (HCC) differentiation using multiphase CT. PubMed. 9(1). 13–22. 7 indexed citations

Carlson, David J., et al.. (2024). Progress Towards Educating the Engineer of 2020. 2021 ASEE Virtual Annual Conference Content Access Proceedings. 1 indexed citations

Zou, Wei, Eric S. Diffenderfer, David J. Carlson, et al.. (2022). A phenomenological model of proton FLASH oxygen depletion effects depending on tissue vasculature and oxygen supply. Frontiers in Oncology. 12. 1004121–1004121. 10 indexed citations

Wright, Christopher M., Michele M. Kim, Emily J. Anstadt, et al.. (2022). Stricter Postoperative Oropharyngeal Cancer Radiation Therapy Normal Tissue Dose Constraints Are Feasible. Practical Radiation Oncology. 12(4). e282–e285.

Paganetti, Harald, Eleanor A. Blakely, Alejandro Cárabe, et al.. (2019). Report of the AAPM TG‐256 on the relative biological effectiveness of proton beams in radiation therapy. Medical Physics. 46(3). e53–e78. 212 indexed citations breakdown →

Yu, James B., T. Beck, Mitchell S. Anscher, et al.. (2019). Analysis of the 2017 American Society for Radiation Oncology (ASTRO) Research Portfolio. International Journal of Radiation Oncology*Biology*Physics. 103(2). 297–304. 4 indexed citations

Guan, Fada, Changran Geng, David J. Carlson, et al.. (2018). A mechanistic relative biological effectiveness model-based biological dose optimization for charged particle radiobiology studies. Physics in Medicine and Biology. 64(1). 15008–15008. 16 indexed citations

Rockwell, Sara, Ming‐Qiang Zheng, Yiyun Huang, et al.. (2017). Quantification of Tumor Hypoxic Fractions Using Positron Emission Tomography with [18F]Fluoromisonidazole ([18F]FMISO) Kinetic Analysis and Invasive Oxygen Measurements. Molecular Imaging and Biology. 19(6). 893–902. 17 indexed citations

Kamp, Florian, David J. Carlson, & Jan J. Wilkens. (2017). Rapid implementation of the repair-misrepair-fixation (RMF) model facilitating online adaption of radiosensitivity parameters in ion therapy. Physics in Medicine and Biology. 62(13). N285–N296. 15 indexed citations

10.

Song, Changhoon, Beom-Ju Hong, Seoyeon Bok, et al.. (2016). Real-time Tumor Oxygenation Changes After Single High-dose Radiation Therapy in Orthotopic and Subcutaneous Lung Cancer in Mice: Clinical Implication for Stereotactic Ablative Radiation Therapy Schedule Optimization. International Journal of Radiation Oncology*Biology*Physics. 95(3). 1022–1031. 28 indexed citations

11.

Zheng, Ming‐Qiang, Frédéric Y. Bois, Jim Ropchan, et al.. (2015). Synthesis of [ 18 F]FMISO in a flow-through microfluidic reactor: Development and clinical application. Nuclear Medicine and Biology. 42(6). 578–584. 19 indexed citations

12.

Feng, Yuanming, Yibao Zhang, Xin Ming, et al.. (2015). Is It the Time for Personalized Imaging Protocols in Cancer Radiation Therapy?. International Journal of Radiation Oncology*Biology*Physics. 91(3). 659–660. 6 indexed citations

13.

Schuemann, Jan, Ilaria Rinaldi, Lucas Burigo, et al.. (2015). Extension of TOPAS for the simulation of proton radiation effects considering molecular and cellular endpoints. Physics in Medicine and Biology. 60(13). 5053–5070. 53 indexed citations

14.

Kamp, Florian, et al.. (2014). Predicting the Relative Biological Effectiveness of Carbon Ion Radiation Therapy Beams Using the Mechanistic Repair-Misrepair-Fixation (RMF) Model and Nuclear Fragment Spectra. International Journal of Radiation Oncology*Biology*Physics. 90(1). S849–S849. 1 indexed citations

15.

Carlson, David J., Kamil M. Yenice, & Colin G. Orton. (2011). Tumor hypoxia is an important mechanism of radioresistance in hypofractionated radiotherapy and must be considered in the treatment planning process. Medical Physics. 38(12). 6347–6350. 34 indexed citations

16.

Yu, Victor K., et al.. (2011). A Mechanism-Based Approach to Predict the Relative Biological Effectiveness of Protons and Carbon Ions in Radiation Therapy. International Journal of Radiation Oncology*Biology*Physics. 83(1). 442–450. 114 indexed citations

17.

Chagpar, Anees B., Charles R. Scoggins, Robert C.G. Martin, et al.. (2006). Predicting Patients at Low Probability of Requiring Postmastectomy Radiation Therapy. Annals of Surgical Oncology. 14(2). 670–677. 35 indexed citations

18.

Chagpar, Anees B., Robert C.G. Martin, Charles R. Scoggins, et al.. (2005). Factors predicting failure to identify a sentinel lymph node in breast cancer. Surgery. 138(1). 56–63. 60 indexed citations

19.

Wong, Sandra L., Celia Chao, Michael J. Edwards, et al.. (2002). Frequency of sentinel lymph node metastases in patients with favorable breast cancer histologic subtypes. The American Journal of Surgery. 184(6). 492–498. 49 indexed citations

20.

McMasters, Kelly M., Sandra L. Wong, Todd M. Tuttle, et al.. (2000). Preoperative Lymphoscintigraphy for Breast Cancer Does Not Improve the Ability to Identify Axillary Sentinel Lymph Nodes. Annals of Surgery. 231(5). 724–731. 132 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.

Explore authors with similar magnitude of impact