M. Rives

808 total citations
9 papers, 252 citations indexed

About

M. Rives is a scholar working on Surgery, Otorhinolaryngology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, M. Rives has authored 9 papers receiving a total of 252 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Surgery, 6 papers in Otorhinolaryngology and 3 papers in Pulmonary and Respiratory Medicine. Recurrent topics in M. Rives's work include Head and Neck Cancer Studies (5 papers), Head and Neck Surgical Oncology (4 papers) and Salivary Gland Tumors Diagnosis and Treatment (2 papers). M. Rives is often cited by papers focused on Head and Neck Cancer Studies (5 papers), Head and Neck Surgical Oncology (4 papers) and Salivary Gland Tumors Diagnosis and Treatment (2 papers). M. Rives collaborates with scholars based in France. M. Rives's co-authors include É. Bardet, Jean Bourhis, M. Lapeyre, J. Tortochaux, P. Wibault, C. Lemanski, M. Juliéron, L. Geoffrois, Antoine Lusinchi and S. Bourdin and has published in prestigious journals such as Journal of Clinical Oncology, Clinical Cancer Research and Cancers.

In The Last Decade

M. Rives

8 papers receiving 245 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
M. Rives France	7	162	116	102	96	50	9	252
Charlotte A.H. Lange Netherlands	8	126 0.8×	57 0.5×	74 0.7×	86 0.9×	61 1.2×	15	209
F. Rosen United States	6	314 1.9×	118 1.0×	152 1.5×	219 2.3×	30 0.6×	10	399
Danita Kannarunimit Thailand	13	296 1.8×	188 1.6×	148 1.5×	146 1.5×	104 2.1×	27	425
Anthony H.P. Tam China	5	201 1.2×	98 0.8×	117 1.1×	127 1.3×	41 0.8×	9	284
Kean Fatt Ho United Kingdom	8	216 1.3×	165 1.4×	74 0.7×	113 1.2×	47 0.9×	9	302
Marzia Franceschini Italy	6	157 1.0×	67 0.6×	65 0.6×	110 1.1×	28 0.6×	15	220
Sarin Kitpanit Thailand	9	148 0.9×	99 0.9×	77 0.8×	62 0.6×	63 1.3×	22	216
Xiao-Yun Li China	10	157 1.0×	81 0.7×	108 1.1×	86 0.9×	38 0.8×	16	248
Asaf Senft Netherlands	8	237 1.5×	92 0.8×	121 1.2×	112 1.2×	111 2.2×	10	306
Olivier Ballivy Canada	8	74 0.5×	92 0.8×	67 0.7×	36 0.4×	48 1.0×	14	194

Countries citing papers authored by M. Rives

Since Specialization

Citations

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

Fields of papers citing papers by M. Rives

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Rives

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

All Works

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9 of 9 papers shown

Giraud, P, Philippe Giraud, M. Alfonsi, et al.. (2020). Interpretable Machine Learning Model for Locoregional Relapse Prediction in Oropharyngeal Cancers. Cancers. 13(1). 57–57. 17 indexed citations

Chabrillac, É., Guillaume de Bonnecaze, M. Rives, et al.. (2019). Endonasal endoscopic oncologic resection and reconstruction of the anterior skull base in the elderly: A single-center retrospective study. European Annals of Otorhinolaryngology Head and Neck Diseases. 137(6). 477–481.

Bonnecaze, Guillaume de, Benjamin Vérillaud, Léonor Chaltiel, et al.. (2018). Clinical characteristics and prognostic factors of sinonasal undifferentiated carcinoma: a multicenter study. International Forum of Allergy & Rhinology. 8(9). 1065–1072. 24 indexed citations

Bibault, Jean‐Emmanuel, Lionel Perrier, P. Pommier, et al.. (2016). Toxicity and efficacy of cetuximab associated with several modalities of IMRT for locally advanced head and neck cancer. Cancer/Radiothérapie. 20(5). 357–361. 9 indexed citations

Querleu, Denis, M. Rives, Manish Chand, & Gwénaël Ferron. (2010). Uterine transposition before radiation therapy in young female rectal cancer patients: A novel technique aimed at preserving fertiliy.. Journal of Clinical Oncology. 28(15_suppl). e19592–e19592. 4 indexed citations

Thomas, Fabienne, Philippe Rochaix, A. Benlyazid, et al.. (2007). Pilot Study of Neoadjuvant Treatment with Erlotinib in Nonmetastatic Head and Neck Squamous Cell Carcinoma. Clinical Cancer Research. 13(23). 7086–7092. 54 indexed citations

Bourhis, Jean, M. Lapeyre, J. Tortochaux, et al.. (2006). Phase III Randomized Trial of Very Accelerated Radiation Therapy Compared With Conventional Radiation Therapy in Squamous Cell Head and Neck Cancer: A GORTEC Trial. Journal of Clinical Oncology. 24(18). 2873–2878. 103 indexed citations

Noël, É., René‐Jean Bensadoun, O. Chapet, et al.. (2006). [The cost of intensity modulated radiation therapy in head and neck cancers: results of the 2002 STIC study].. PubMed. 93(10). 1026–32. 10 indexed citations

Bourhis, Jean, G. Calais, M. Lapeyre, et al.. (2004). Concomitant radiochemotherapy or accelerated radiotherapy: Analysis of two randomized trials of the French Head and Neck Cancer Group (GORTEC). Seminars in Oncology. 31(6). 822–826. 31 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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