Gustavo Mercier

1.9k total citations
42 papers, 1.4k citations indexed

About

Gustavo Mercier is a scholar working on Radiology, Nuclear Medicine and Imaging, Otorhinolaryngology and Surgery. According to data from OpenAlex, Gustavo Mercier has authored 42 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Radiology, Nuclear Medicine and Imaging, 10 papers in Otorhinolaryngology and 8 papers in Surgery. Recurrent topics in Gustavo Mercier's work include Radiomics and Machine Learning in Medical Imaging (18 papers), Medical Imaging Techniques and Applications (14 papers) and Head and Neck Cancer Studies (10 papers). Gustavo Mercier is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (18 papers), Medical Imaging Techniques and Applications (14 papers) and Head and Neck Cancer Studies (10 papers). Gustavo Mercier collaborates with scholars based in United States, Japan and Belgium. Gustavo Mercier's co-authors include Rathan M. Subramaniam, Patrick J. Peller, Elizabeth H. Dibble, E. Francis Cook, Osamu Sakai, Devaki Shilpa Surasi, Jessica Davison, Minh Tam Truong, Gregory A. Russo and Jeffrey S. Berman and has published in prestigious journals such as SHILAP Revista de lepidopterología, Radiology and International Journal of Molecular Sciences.

In The Last Decade

Gustavo Mercier

42 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gustavo Mercier United States 20 723 462 339 276 240 42 1.4k
Ronan Abgral France 25 968 1.3× 549 1.2× 335 1.0× 360 1.3× 356 1.5× 122 1.7k
Ie Ryung Yoo South Korea 21 514 0.7× 495 1.1× 317 0.9× 133 0.5× 317 1.3× 90 1.3k
Ivan Platzek Germany 22 599 0.8× 512 1.1× 235 0.7× 95 0.3× 126 0.5× 81 1.3k
Jiho Nam South Korea 11 901 1.2× 1.4k 2.9× 540 1.6× 511 1.9× 327 1.4× 39 2.5k
Francesco Fiz Italy 19 583 0.8× 435 0.9× 292 0.9× 50 0.2× 354 1.5× 95 1.2k
Hisao Tonami Japan 23 1.3k 1.8× 1.1k 2.4× 417 1.2× 90 0.3× 276 1.1× 81 2.5k
Jae Myoung Noh South Korea 21 242 0.3× 602 1.3× 371 1.1× 168 0.6× 557 2.3× 112 1.5k
Ryo Toya Japan 18 545 0.8× 264 0.6× 251 0.7× 175 0.6× 206 0.9× 86 1.3k
Édith Filion Canada 21 598 0.8× 756 1.6× 352 1.0× 372 1.3× 233 1.0× 74 1.4k
Avi Eisbruch United States 7 442 0.6× 528 1.1× 190 0.6× 178 0.6× 123 0.5× 7 1.0k

Countries citing papers authored by Gustavo Mercier

Since Specialization
Citations

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

Fields of papers citing papers by Gustavo Mercier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gustavo Mercier

This figure shows the co-authorship network connecting the top 25 collaborators of Gustavo Mercier. A scholar is included among the top collaborators of Gustavo Mercier 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 Gustavo Mercier. Gustavo Mercier 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.
Tripodis, Yorghos, Michael L. Alosco, Jesse Mez, et al.. (2023). Annualized changes in rate of amyloid deposition and neurodegeneration are greater in participants who become amyloid positive than those who remain amyloid negative. Neurobiology of Aging. 127. 33–42. 3 indexed citations
2.
Staziaki, Pedro V., et al.. (2023). Hematocrit and lactate trends help predict outcomes in trauma independent of CT and other clinical parameters. SHILAP Revista de lepidopterología. 3. 1186277–1186277. 1 indexed citations
3.
Fujima, Noriyuki, V. Carlota Andreu‐Arasa, Gustavo Mercier, et al.. (2021). Prediction of the local treatment outcome in patients with oropharyngeal squamous cell carcinoma using deep learning analysis of pretreatment FDG-PET images. BMC Cancer. 21(1). 900–900. 18 indexed citations
4.
Fujima, Noriyuki, V. Carlota Andreu‐Arasa, Gustavo Mercier, et al.. (2020). Deep learning analysis using FDG-PET to predict treatment outcome in patients with oral cavity squamous cell carcinoma. European Radiology. 30(11). 6322–6330. 34 indexed citations
5.
6.
Acuña-Villaorduña, Carlos, Gustavo Mercier, Mary B. Kleinman, et al.. (2018). FDG-PET/CT activity leads to the diagnosis of unsuspected TB: a retrospective study. BMC Research Notes. 11(1). 464–464. 11 indexed citations
7.
Sridhar, Praveen, et al.. (2014). FDG PET Metabolic Tumor Volume Segmentation and Pathologic Volume of Primary Human Solid Tumors. American Journal of Roentgenology. 202(5). 1114–1119. 66 indexed citations
8.
Ashley, Brogan, Jeffrey S. Berman, Aaron L. Sverdlov, et al.. (2014). Quantitative interpretation of FDG PET/CT with myocardial perfusion imaging increases diagnostic information in the evaluation of cardiac sarcoidosis. Journal of Nuclear Cardiology. 21(5). 925–939. 141 indexed citations
9.
Mercier, Gustavo, et al.. (2014). Interreader Agreement and Variability of FDG PET Volumetric Parameters in Human Solid Tumors. American Journal of Roentgenology. 202(2). 406–412. 17 indexed citations
10.
Surasi, Devaki Shilpa, Patrick J. Peller, Zsolt Szabó, Gustavo Mercier, & Rathan M. Subramaniam. (2013). Dopamine Transporter SPECT Imaging in Parkinson Disease and Dementia. PET Clinics. 8(4). 459–467. 4 indexed citations
11.
Subramaniam, Rathan M., et al.. (2013). Impact of Concurrent Diagnostic Level CT With PET/CT on the Utilization of Stand-Alone CT and MRI in the Management of Head and Neck Cancer Patients. Clinical Nuclear Medicine. 38(10). 790–794. 10 indexed citations
12.
Mirpour, Sahar, et al.. (2013). The Role of PET/CT in the Management of Cervical Cancer. American Journal of Roentgenology. 201(2). W192–W205. 51 indexed citations
13.
Shah, Bhavya, et al.. (2012). Intra-reader reliability of FDG PET volumetric tumor parameters: effects of primary tumor size and segmentation methods. Annals of Nuclear Medicine. 26(9). 707–714. 30 indexed citations
14.
Mercier, Gustavo, et al.. (2012). FDG PET/CT interobserver agreement in head and neck cancer. Nuclear Medicine Communications. 33(3). 305–312. 28 indexed citations
15.
Dibble, Elizabeth H., et al.. (2012). 18F-FDG Metabolic Tumor Volume and Total Glycolytic Activity of Oral Cavity and Oropharyngeal Squamous Cell Cancer: Adding Value to Clinical Staging. Journal of Nuclear Medicine. 53(5). 709–715. 193 indexed citations
16.
Peller, Patrick J., et al.. (2011). Value of PET/CT in the Management of Primary Hepatobiliary Tumors, Part 2. American Journal of Roentgenology. 197(2). W260–W265. 79 indexed citations
17.
Subramaniam, Rathan M., et al.. (2009). Fluorodeoxyglucose–Positron-Emission Tomography Imaging of Head and Neck Squamous Cell Cancer. American Journal of Neuroradiology. 31(4). 598–604. 89 indexed citations
18.
19.
Mercier, Gustavo. (1998). Enhancing the relaxivity of paramagnetic coordination complexes through the optimization of the molecular electrostatic potential. Magnetic Resonance Imaging. 16(7). 811–828. 5 indexed citations
20.
Mercier, Gustavo. (1995). On the molecular spin density and the electrostatic potential as determinants of the relaxivity of metalloporphyrins. Magnetic Resonance Imaging. 13(6). 807–817. 5 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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