David C. Newitt

5.9k total citations
100 papers, 4.4k citations indexed

About

David C. Newitt is a scholar working on Radiology, Nuclear Medicine and Imaging, Orthopedics and Sports Medicine and Biomedical Engineering. According to data from OpenAlex, David C. Newitt has authored 100 papers receiving a total of 4.4k indexed citations (citations by other indexed papers that have themselves been cited), including 67 papers in Radiology, Nuclear Medicine and Imaging, 40 papers in Orthopedics and Sports Medicine and 14 papers in Biomedical Engineering. Recurrent topics in David C. Newitt's work include MRI in cancer diagnosis (41 papers), Bone health and osteoporosis research (38 papers) and Radiomics and Machine Learning in Medical Imaging (33 papers). David C. Newitt is often cited by papers focused on MRI in cancer diagnosis (41 papers), Bone health and osteoporosis research (38 papers) and Radiomics and Machine Learning in Medical Imaging (33 papers). David C. Newitt collaborates with scholars based in United States, Germany and Sweden. David C. Newitt's co-authors include Sharmila Majumdar, Harry K. Genant, Thomas M. Link, John C. Lin, Nola M. Hylton, S. Grampp, Anil Mathur, Ying Lü, Peter Augat and Alice Gies and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

David C. Newitt

100 papers receiving 4.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David C. Newitt United States 39 2.1k 2.1k 841 705 473 100 4.4k
Marc‐André Weber Germany 40 2.2k 1.0× 580 0.3× 677 0.8× 1.3k 1.9× 368 0.8× 344 6.2k
Jan S. Bauer Germany 36 946 0.4× 1.5k 0.7× 1.0k 1.2× 1.2k 1.8× 186 0.4× 121 4.0k
Stefan Delorme Germany 53 4.1k 1.9× 492 0.2× 1.6k 1.9× 1.7k 2.4× 1.5k 3.1× 316 9.1k
Julio Carballido‐Gamio United States 38 1.0k 0.5× 1.3k 0.6× 1.4k 1.6× 1.9k 2.7× 135 0.3× 96 4.1k
Dianna D. Cody United States 43 3.0k 1.4× 899 0.4× 2.5k 3.0× 1.2k 1.7× 530 1.1× 147 5.7k
David L. Buckley United Kingdom 46 7.0k 3.3× 282 0.1× 550 0.7× 324 0.5× 321 0.7× 132 8.4k
Nandita M. deSouza United Kingdom 48 3.9k 1.8× 208 0.1× 473 0.6× 1.2k 1.7× 958 2.0× 208 7.3k
Jiang Du United States 44 3.9k 1.8× 1.6k 0.8× 1.5k 1.7× 1.3k 1.9× 72 0.2× 245 6.4k
Shonit Punwani United Kingdom 42 3.0k 1.4× 183 0.1× 511 0.6× 1.0k 1.4× 348 0.7× 196 6.1k
Joan C. Vilanova Spain 34 1.3k 0.6× 188 0.1× 408 0.5× 410 0.6× 246 0.5× 143 3.6k

Countries citing papers authored by David C. Newitt

Since Specialization
Citations

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

Fields of papers citing papers by David C. Newitt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David C. Newitt

This figure shows the co-authorship network connecting the top 25 collaborators of David C. Newitt. A scholar is included among the top collaborators of David C. Newitt 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 C. Newitt. David C. Newitt 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.
Chitalia, Rhea, Nariman Jahani, Spyros Tastsoglou, et al.. (2023). Radiomic tumor phenotypes augment molecular profiling in predicting recurrence free survival after breast neoadjuvant chemotherapy. SHILAP Revista de lepidopterología. 3(1). 46–46. 5 indexed citations
2.
Li, Wen, Natsuko Onishi, David C. Newitt, et al.. (2022). Diffusion-Weighted MRI for Predicting Pathologic Complete Response in Neoadjuvant Immunotherapy. Cancers. 14(18). 4436–4436. 14 indexed citations
3.
Chitalia, Rhea, Sarthak Pati, Siddhesh Thakur, et al.. (2022). Expert tumor annotations and radiomics for locally advanced breast cancer in DCE-MRI for ACRIN 6657/I-SPY1. Scientific Data. 9(1). 440–440. 10 indexed citations
4.
Partridge, Savannah C., Jon A. Steingrimsson, David C. Newitt, et al.. (2022). Impact of Alternate b-Value Combinations and Metrics on the Predictive Performance and Repeatability of Diffusion-Weighted MRI in Breast Cancer Treatment: Results from the ECOG-ACRIN A6698 Trial. Tomography. 8(2). 701–717. 7 indexed citations
5.
6.
7.
Onishi, Natsuko, Jessica Gibbs, Wen Li, et al.. (2022). Abstract P3-03-01: Functional tumor volume at 3 and 6-week MRI as an indicator of patients with inferior outcome after neoadjuvant chemotherapy. Cancer Research. 82(4_Supplement). P3–3. 1 indexed citations
8.
Newitt, David C., Savannah C. Partridge, Helga S. Marques, et al.. (2020). Repeatability and Reproducibility of ADC Histogram Metrics from the ACRIN 6698 Breast Cancer Therapy Response Trial. Tomography. 6(2). 177–185. 11 indexed citations
9.
Onishi, Natsuko, Wen Li, Jessica Gibbs, et al.. (2020). Impact of MRI Protocol Adherence on Prediction of Pathological Complete Response in the I-SPY 2 Neoadjuvant Breast Cancer Trial. Tomography. 6(2). 77–85. 7 indexed citations
10.
Lo, Wei‐Ching, Wen Li, Ella F. Jones, et al.. (2016). Effect of Imaging Parameter Thresholds on MRI Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Subtypes. PLoS ONE. 11(2). e0142047–e0142047. 11 indexed citations
11.
Aliu, Sheye O., Ella F. Jones, John Kornak, et al.. (2014). Repeatability of Quantitative MRI Measurements in Normal Breast Tissue. Translational Oncology. 7(1). 130–137. 19 indexed citations
12.
Black, Dennis M., Mary Bouxsein, Lisa Palermo, et al.. (2008). Randomized Trial of Once-Weekly Parathyroid Hormone (1-84) on Bone Mineral Density and Remodeling. The Journal of Clinical Endocrinology & Metabolism. 93(6). 2166–2172. 40 indexed citations
13.
Carballido‐Gamio, Julio, Duan Xu, David C. Newitt, et al.. (2006). Single-shot fast spin-echo diffusion tensor imaging of the lumbar spine at 1.5 and 3 T. Magnetic Resonance Imaging. 25(5). 665–670. 16 indexed citations
14.
Link, Thomas M., Carole Phan, David C. Newitt, et al.. (2005). 3.0 vs 1.5 T MRI in the detection of focal cartilage pathology – ROC analysis in an experimental model. Osteoarthritis and Cartilage. 14(1). 63–70. 68 indexed citations
15.
Newitt, David C., et al.. (2005). T1rho relaxation quantification using spiral imaging: a preliminary study. PubMed. 3. 1032–1035. 6 indexed citations
16.
Newitt, David C., Ying Lü, Brian MacDonald, Sharmila Majumdar, & Laurent Pothuaud. (2004). In vivo application of 3D-line skeleton graph analysis (LSGA) technique with high-resolution magnetic resonance imaging of trabecular bone structure. Osteoporosis International. 15(5). 411–419. 17 indexed citations
17.
Link, Thomas M., Volker Vieth, Christoph Stehling, et al.. (2003). High-resolution MRI vs multislice spiral CT: Which technique depicts the trabecular bone structure best?. European Radiology. 13(4). 663–671. 84 indexed citations
18.
Yonelinas, Andrew P., Tracy Luks, David C. Newitt, et al.. (2002). Dissociating perceptual and conceptual implicit memory in multiple sclerosis patients. Brain and Cognition. 50(1). 51–61. 20 indexed citations
19.
Link, Thomas M., et al.. (1998). Computergestützte Strukturanalyse des trabekulären Knochens in der Osteoporosediagnostik. Der Radiologe. 38(10). 853–859. 5 indexed citations
20.
Majumdar, Sharmila, David C. Newitt, Anil Mathur, et al.. (1996). Magnetic resonance imaging of trabecular bone structure in the distal radius: Relationship with X-ray tomographic microscopy and biomechanics. Osteoporosis International. 6(5). 376–385. 146 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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