Benjamin Lacas

3.2k citations
28 papers · 545 · h-index 9

Impact in

Papers in

Benjamin Lacas

26 papers receiving 543 citations

Peers

Benjamin Lacas
Comparison fields: 5 of 45
  • Otorhinolaryngology 250
  • Pulmonary and Respiratory Medicine 201
  • Oncology 146
  • Cancer Research 58
  • Surgery 96
Replace Maria Grazia Ghi with:
Maria Grazia Ghi Italy
Joseph Wee Singapore
To Wai Leung China
O S.K. China
Anne Moxhon Belgium
Yan Mao China
Brita B. Jensen Denmark
S G Taylor United Kingdom
João Luís Fernandes da Silva Brazil
D. Spielsinger United States
Benjamin Lacas relative to Maria Grazia Ghi Italy Maria Grazia Ghi's profile →
Citations per field
00.5×3.1×
Maria Grazia Ghi · 1×
Citations per year

Countries citing papers authored by Benjamin Lacas

Since Specialization
Citations

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

Fields of papers citing papers by Benjamin Lacas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Benjamin Lacas, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Benjamin Lacas Line = papers co-authored together Benjamin Lacas links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013187
2 201795
3 201779
4 201679
5 201820
6 201613
7 201312
8 201711
9 20138
10 20216
11 20156
12 20175
13 20224
14 20183
15 20142
16 20152
17 20182
18 20192
19 20122
20 20231

About Benjamin Lacas

Benjamin Lacas is a scholar working on Pulmonary and Respiratory Medicine, Otorhinolaryngology, Oncology, Surgery and Radiology, Nuclear Medicine and Imaging, having authored 28 papers that have together received 545 indexed citations. Recurring topics across this work include Head and Neck Cancer Studies (7 papers), Lung Cancer Treatments and Mutations (6 papers), Lung Cancer Diagnosis and Treatment (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Sarcoma Diagnosis and Treatment (2 papers), Hepatocellular Carcinoma Treatment and Prognosis (2 papers), Uterine Myomas and Treatments (2 papers) and Vascular Tumors and Angiosarcomas (2 papers). The work is most often cited by research in Otorhinolaryngology (250 citations), Pulmonary and Respiratory Medicine (201 citations), Oncology (146 citations), Cancer Research (58 citations) and Surgery (96 citations). Benjamin Lacas has collaborated with scholars based in France, United States and Canada. Frequent co-authors include Jean‐Pierre Pignon, Pierre Blanchard, Jean Bourhis, Marshall R. Posner, Jan B. Vermorken, Juan Jesús Cruz, Adriano Paccagnella, Abderrahmane Bourredjem, Ricardo Hitt and G. Calais. Their work appears in journals such as Radiotherapy and Oncology, Journal of Clinical Oncology, Annals of Oncology, European Journal of Cancer and Oncotarget.

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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