Jill Fredrickson

2.1k total citations
33 papers, 1.2k citations indexed

About

Jill Fredrickson is a scholar working on Radiology, Nuclear Medicine and Imaging, Molecular Biology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Jill Fredrickson has authored 33 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Radiology, Nuclear Medicine and Imaging, 11 papers in Molecular Biology and 9 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Jill Fredrickson's work include Radiomics and Machine Learning in Medical Imaging (7 papers), Advanced MRI Techniques and Applications (7 papers) and Medical Imaging Techniques and Applications (6 papers). Jill Fredrickson is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (7 papers), Advanced MRI Techniques and Applications (7 papers) and Medical Imaging Techniques and Applications (6 papers). Jill Fredrickson collaborates with scholars based in United States, Switzerland and Australia. Jill Fredrickson's co-authors include Norbert J. Pelc, Robert J. Herfkens, H. Wegmüller, Alex de Crespigny, Alex M. DePaoli, Linda S. Higgins, F. L. Dunn, Johanna C. Bendell, Bryan D. Myers and Jennifer Lauchle and has published in prestigious journals such as Journal of Clinical Oncology, Blood and Hepatology.

In The Last Decade

Jill Fredrickson

33 papers receiving 1.2k citations

Peers

Jill Fredrickson
Yanling Wang China
Min Ren United States
Siân Griffin United Kingdom
Sabine Leh Norway
Andrew Gaya United Kingdom
Ian Rabinowitz United States
Catherine Mitchell Australia
Richard Bitar Canada
Giovanni Storto Italy
Yanling Wang China
Jill Fredrickson
Citations per year, relative to Jill Fredrickson Jill Fredrickson (= 1×) peers Yanling Wang

Countries citing papers authored by Jill Fredrickson

Since Specialization
Citations

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

Fields of papers citing papers by Jill Fredrickson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jill Fredrickson

This figure shows the co-authorship network connecting the top 25 collaborators of Jill Fredrickson. A scholar is included among the top collaborators of Jill Fredrickson 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 Jill Fredrickson. Jill Fredrickson 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.
Fredrickson, Jill, et al.. (2025). Comparative analysis of intestinal tumor segmentation in PET CT scans using organ based and whole body deep learning. BMC Medical Imaging. 25(1). 52–52. 1 indexed citations
2.
Chandarlapaty, Sarat, Maura N. Dickler, José Alejandro Pérez Fidalgo, et al.. (2023). An Open-label Phase I Study of GDC-0927 in Postmenopausal Women with Locally Advanced or Metastatic Estrogen Receptor–Positive Breast Cancer. Clinical Cancer Research. 29(15). 2781–2790. 7 indexed citations
3.
Lian, Qinshu, Jill Fredrickson, Christiane Rothkegel, et al.. (2023). Meta-Analysis of 49 Roche Oncology Trials Comparing Blinded Independent Central Review (BICR) and Local Evaluation to Assess the Value of BICR. The Oncologist. 29(8). e1073–e1081. 5 indexed citations
4.
Bardia, Aditya, Ingrid A. Mayer, Eric P. Winer, et al.. (2022). The oral selective estrogen receptor degrader GDC-0810 (ARN-810) in postmenopausal women with hormone receptor-positive HER2-negative (HR + /HER2 −) advanced/metastatic breast cancer. Breast Cancer Research and Treatment. 197(2). 319–331. 14 indexed citations
5.
Fredrickson, Jill, et al.. (2020). Tumor Segmentation and Feature Extraction from Whole-Body FDG-PET/CT Using Cascaded 2D and 3D Convolutional Neural Networks. Journal of Digital Imaging. 33(4). 888–894. 51 indexed citations
6.
Shapiro, Geoffrey I., Patricia LoRusso, Eunice L. Kwak, et al.. (2019). Phase Ib study of the MEK inhibitor cobimetinib (GDC-0973) in combination with the PI3K inhibitor pictilisib (GDC-0941) in patients with advanced solid tumors. Investigational New Drugs. 38(2). 419–432. 73 indexed citations
7.
Spigel, David R., Jamie E. Chaft, Scott Gettinger, et al.. (2018). FIR: Efficacy, Safety, and Biomarker Analysis of a Phase II Open-Label Study of Atezolizumab in PD-L1–Selected Patients With NSCLC. Journal of Thoracic Oncology. 13(11). 1733–1742. 114 indexed citations
8.
Weekes, Colin D., Lee S. Rosen, Anna Capasso, et al.. (2018). Phase I study of the anti-α5β1 monoclonal antibody MINT1526A with or without bevacizumab in patients with advanced solid tumors. Cancer Chemotherapy and Pharmacology. 82(2). 339–351. 15 indexed citations
9.
Dolly, Saoirse, Andrew J. Wagner, Johanna C. Bendell, et al.. (2016). Phase I Study of Apitolisib (GDC-0980), Dual Phosphatidylinositol-3-Kinase and Mammalian Target of Rapamycin Kinase Inhibitor, in Patients with Advanced Solid Tumors. Clinical Cancer Research. 22(12). 2874–2884. 105 indexed citations
10.
Wachenfeldt, Karin von, Jacob Fog Bentzon, Lars B. Nielsen, et al.. (2016). Treatment with a human recombinant monoclonal IgG antibody against oxidized LDL in atherosclerosis-prone pigs reduces cathepsin S in coronary lesions. International Journal of Cardiology. 215. 506–515. 17 indexed citations
11.
12.
Emami, Hamed, Parmanand Singh, Megan H. MacNabb, et al.. (2015). Splenic Metabolic Activity Predicts Risk of Future Cardiovascular Events. JACC. Cardiovascular imaging. 8(2). 121–130. 197 indexed citations
13.
Puzanov, Igor, Grant A. McArthur, René González, et al.. (2014). Updated results and correlative FDG-PET analysis of a phase IB study of vemurafenib and cobimetinib (MEK inhibitor [GDC-0973]), in advanced BRAFV600- mutated melanoma (BRIM7). Journal of Translational Medicine. 12(Suppl 1). O7–O7. 6 indexed citations
14.
15.
Dunn, F. L., Linda S. Higgins, Jill Fredrickson, & Alex M. DePaoli. (2010). Selective modulation of PPARγ activity can lower plasma glucose without typical thiazolidinedione side-effects in patients with Type 2 diabetes. Journal of Diabetes and its Complications. 25(3). 151–158. 67 indexed citations
16.
Sommer, Graham, Jill Fredrickson, Anne M. Sawyer-Glover, et al.. (1998). Renal blood flow: measurement in vivo with rapid spiral MR imaging.. Radiology. 208(3). 729–734. 33 indexed citations
17.
Fredrickson, Jill, H. Wegmüller, Robert J. Herfkens, & Norbert J. Pelc. (1995). Simultaneous temporal resolution of cardiac and respiratory motion in MR imaging.. Radiology. 195(1). 169–175. 37 indexed citations
18.
Li, King C., Charles H. McDonnell, Jill Fredrickson, et al.. (1994). Chronic mesenteric ischemia: evaluation with phase-contrast cine MR imaging.. Radiology. 190(1). 175–179. 58 indexed citations
19.
Debatin, J. F., R. Ting, H. Wegmüller, et al.. (1994). Renal artery blood flow: quantitation with phase-contrast MR imaging with and without breath holding.. Radiology. 190(2). 371–378. 110 indexed citations
20.
Fredrickson, Jill & Norbert J. Pelc. (1994). Time‐resolved MR imaging by automatic data segmentation. Journal of Magnetic Resonance Imaging. 4(2). 189–196. 22 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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