Jean‐Louis Alberini

2.9k total citations
65 papers, 1.9k citations indexed

About

Jean‐Louis Alberini is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Oncology. According to data from OpenAlex, Jean‐Louis Alberini has authored 65 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Radiology, Nuclear Medicine and Imaging, 19 papers in Pulmonary and Respiratory Medicine and 19 papers in Oncology. Recurrent topics in Jean‐Louis Alberini's work include Medical Imaging Techniques and Applications (24 papers), Radiomics and Machine Learning in Medical Imaging (16 papers) and Breast Cancer Treatment Studies (9 papers). Jean‐Louis Alberini is often cited by papers focused on Medical Imaging Techniques and Applications (24 papers), Radiomics and Machine Learning in Medical Imaging (16 papers) and Breast Cancer Treatment Studies (9 papers). Jean‐Louis Alberini collaborates with scholars based in France, United States and Germany. Jean‐Louis Alberini's co-authors include Myriam Wartski, A Pecking, Elise Le Stanc, É. Gontier, Emmanuelle Fourme, Véronique Edeline, Florence Lerebours, Lars-Eric Adam, Marc Hickeson and Alexandre Cochet and has published in prestigious journals such as Journal of Clinical Oncology, The Journal of Clinical Endocrinology & Metabolism and Cancer.

In The Last Decade

Jean‐Louis Alberini

57 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jean‐Louis Alberini France 27 810 573 501 469 407 65 1.9k
Jeffrey Meyer United States 23 557 0.7× 621 1.1× 790 1.6× 573 1.2× 227 0.6× 125 2.3k
Nicolas Aide France 29 1.6k 2.0× 678 1.2× 939 1.9× 440 0.9× 174 0.4× 107 2.8k
Christine Sagan France 25 468 0.6× 622 1.1× 770 1.5× 632 1.3× 763 1.9× 101 2.4k
Max Seidensticker Germany 27 689 0.9× 806 1.4× 788 1.6× 985 2.1× 279 0.7× 197 3.1k
Kwan Ho Cho South Korea 29 755 0.9× 637 1.1× 1.3k 2.7× 538 1.1× 320 0.8× 104 2.6k
Klaus Zöphel Germany 29 1.3k 1.6× 404 0.7× 905 1.8× 287 0.6× 424 1.0× 108 2.4k
Rodolfo Núñez United States 18 529 0.7× 499 0.9× 671 1.3× 358 0.8× 168 0.4× 41 1.6k
Helmut Dittmann Germany 20 994 1.2× 371 0.6× 585 1.2× 157 0.3× 323 0.8× 84 1.7k
Alexander Becherer Austria 24 853 1.1× 395 0.7× 737 1.5× 693 1.5× 245 0.6× 65 2.3k
Wendy Hayes United States 19 878 1.1× 1.1k 2.0× 1.0k 2.1× 414 0.9× 283 0.7× 54 2.6k

Countries citing papers authored by Jean‐Louis Alberini

Since Specialization
Citations

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

Fields of papers citing papers by Jean‐Louis Alberini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean‐Louis Alberini. 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 Jean‐Louis Alberini. The network helps show where Jean‐Louis Alberini may publish in the future.

Co-authorship network of co-authors of Jean‐Louis Alberini

This figure shows the co-authorship network connecting the top 25 collaborators of Jean‐Louis Alberini. A scholar is included among the top collaborators of Jean‐Louis Alberini 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 Jean‐Louis Alberini. Jean‐Louis Alberini 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.
Samson, Maxime, Isabelle Fournel, Abderrahmane Bourredjem, et al.. (2025). Immediate versus gradual Tocilizu M ab discontinuAtion in G I ant Cell Arteritis: protocol of the multicentre randomised open-label MAGICA trial. BMJ Open. 15(10). e108115–e108115.
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Alberini, Jean‐Louis, André Ramon, H. Devilliers, et al.. (2024). An overview of 18F-fluorodeoxyglucose positron emission tomography/computed tomography in giant cell arteritis. Frontiers in Medicine. 11. 1469964–1469964. 1 indexed citations
5.
Presles, Benoît, Sarah Leclerc, Fabrice Mériaudeau, et al.. (2023). A Tumour and Liver Automatic Segmentation (ATLAS) Dataset on Contrast-Enhanced Magnetic Resonance Imaging for Hepatocellular Carcinoma. Data. 8(5). 79–79. 28 indexed citations
6.
Ladoire, Sylvain, et al.. (2023). Performance of [18F]FDG-PET/CT Imaging in First Recurrence of Invasive Lobular Carcinoma. Journal of Clinical Medicine. 12(8). 2916–2916. 5 indexed citations
7.
Gennari, Alessandra, Étienne Brain, Andrea De Censi, et al.. (2023). Early prediction of endocrine responsiveness in ER+/HER2 negative MBC: Pilot study with 18F-fluoroestradiol (18F-FES) CT/PET.. Journal of Clinical Oncology. 41(16_suppl). 1024–1024.
8.
Beltjens, Françoise, et al.. (2023). Abstract P5-01-11: Utility of 18F-FDG PET/CT for the prediction of pathologic complete response in axilla to neoadjuvant chemotherapy in breast cancer. Cancer Research. 83(5_Supplement). P5–1. 1 indexed citations
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Devilliers, H., André Ramon, Yannick Béjot, et al.. (2022). PET/CT of cranial arteries for a sensitive diagnosis of giant cell arteritis. Lara D. Veeken. 62(4). 1568–1575. 21 indexed citations
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Boughdad, Sarah, Laurence Champion, Véronique Becette, et al.. (2020). Early metabolic response of breast cancer to neoadjuvant endocrine therapy: comparison to morphological and pathological response. Cancer Imaging. 20(1). 11–11. 7 indexed citations
13.
Champion, Laurence, Florence Lerebours, Jean‐Louis Alberini, et al.. (2015). 18F-FDG PET/CT to Predict Response to Neoadjuvant Chemotherapy and Prognosis in Inflammatory Breast Cancer. Journal of Nuclear Medicine. 56(9). 1315–1321. 29 indexed citations
14.
Champion, Laurence, Étienne Brain, Anne‐Laure Giraudet, et al.. (2010). Breast cancer recurrence diagnosis suspected on tumor marker rising. Cancer. 117(8). 1621–1629. 64 indexed citations
15.
Groussin, Lionel, G. Bonardel, S. Silvera, et al.. (2009). 18F-Fluorodeoxyglucose Positron Emission Tomography for the Diagnosis of Adrenocortical Tumors: A Prospective Study in 77 Operated Patients. The Journal of Clinical Endocrinology & Metabolism. 94(5). 1713–1722. 138 indexed citations
16.
Alberini, Jean‐Louis, Florence Lerebours, Myriam Wartski, et al.. (2009). 18F‐fluorodeoxyglucose positron emission tomography/computed tomography (FDG‐PET/CT) imaging in the staging and prognosis of inflammatory breast cancer. Cancer. 115(21). 5038–5047. 94 indexed citations
17.
Alberini, Jean‐Louis, Myriam Wartski, É. Gontier, et al.. (2007). Place de l’imagerie par Tomographie par Émission de Positons pour les tumeurs stromales gastro-intestinales. Gastroentérologie Clinique et Biologique. 31(6-7). 585–593. 18 indexed citations
18.
Alavi, Abass, Naresh C. Gupta, Jean‐Louis Alberini, et al.. (2002). Positron emission tomography imaging in nonmalignant thoracic disorders. Seminars in Nuclear Medicine. 32(4). 293–321. 174 indexed citations
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Alberini, Jean‐Louis, et al.. (2001). Technetium‐99m HMPAO‐Labeled Leukocyte Imaging Compared with Endoscopy, Ultrasonography, and Contrast Radiology in Children with Inflammatory Bowel Disease. Journal of Pediatric Gastroenterology and Nutrition. 32(3). 278–286.
20.
Alberini, Jean‐Louis, Jean-Louis Lefaix, J.Y. Bansard, & P. Bourguet. (2000). Imaging Radiation Induced Muscular Necrosis with Antimyosin-Scintigraphy and Computed Tomography. Health Physics. 78(1). 53–59. 1 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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