Kevin Lamote

885 total citations
34 papers, 582 citations indexed

About

Kevin Lamote is a scholar working on Biomedical Engineering, Pulmonary and Respiratory Medicine and Electrical and Electronic Engineering. According to data from OpenAlex, Kevin Lamote has authored 34 papers receiving a total of 582 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Biomedical Engineering, 12 papers in Pulmonary and Respiratory Medicine and 6 papers in Electrical and Electronic Engineering. Recurrent topics in Kevin Lamote's work include Advanced Chemical Sensor Technologies (21 papers), Gas Sensing Nanomaterials and Sensors (6 papers) and Biosensors and Analytical Detection (5 papers). Kevin Lamote is often cited by papers focused on Advanced Chemical Sensor Technologies (21 papers), Gas Sensing Nanomaterials and Sensors (6 papers) and Biosensors and Analytical Detection (5 papers). Kevin Lamote collaborates with scholars based in Belgium, Australia and United Kingdom. Kevin Lamote's co-authors include Jan P. van Meerbeeck, Eline Janssens, Adda Athanasopoulos-Zekkos, George Athanasopoulos, Kristiaan Nackaerts, Benedicte Y. De Winter, Olivier Thas, Matthijs Vynck, Thérèse Lapperre and Karim Vermaelen and has published in prestigious journals such as Gastroenterology, Journal of Materials Chemistry and Annals of Oncology.

In The Last Decade

Kevin Lamote

32 papers receiving 572 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kevin Lamote Belgium 14 323 151 100 98 86 34 582
Inta Liepniece‐Karele Latvia 12 185 0.6× 208 1.4× 92 0.9× 71 0.7× 58 0.7× 34 596
Armands Sīviņš Latvia 9 335 1.0× 84 0.6× 100 1.0× 120 1.2× 98 1.1× 19 508
Ivars Tolmanis Latvia 13 183 0.6× 190 1.3× 60 0.6× 56 0.6× 51 0.6× 31 510
Meike Hengst Germany 10 127 0.4× 314 2.1× 72 0.7× 60 0.6× 36 0.4× 17 522
Giulia Sedda Italy 13 286 0.9× 196 1.3× 102 1.0× 145 1.5× 87 1.0× 46 578
Aigars Vanags Latvia 10 155 0.5× 140 0.9× 50 0.5× 46 0.5× 38 0.4× 19 386
Arnis Kiršners Latvia 7 143 0.4× 82 0.5× 54 0.5× 48 0.5× 37 0.4× 10 296
Inbar Nardi Agmon Israel 7 159 0.5× 33 0.2× 44 0.4× 75 0.8× 46 0.5× 22 246
Ruchi Sharma United States 9 169 0.5× 33 0.2× 32 0.3× 78 0.8× 69 0.8× 20 317
Alison Burklund United States 10 231 0.7× 8 0.1× 136 1.4× 26 0.3× 32 0.4× 15 393

Countries citing papers authored by Kevin Lamote

Since Specialization
Citations

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

Fields of papers citing papers by Kevin Lamote

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kevin Lamote

This figure shows the co-authorship network connecting the top 25 collaborators of Kevin Lamote. A scholar is included among the top collaborators of Kevin Lamote 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 Kevin Lamote. Kevin Lamote 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.
Wener, Reinier, Jan P. van Meerbeeck, Jo Raskin, et al.. (2025). Differentiating benign and malignant solitary pulmonary nodules through exhaled breath analysis. ERJ Open Research. 12(1). 827–2025.
2.
Janssens, Eline, Tom Richart, Veerle Surmont, et al.. (2023). Determining the clinical utility of a breath test for screening an asbestos-exposed population for pleural mesothelioma: baseline results. Journal of Breath Research. 17(4). 47105–47105. 5 indexed citations
3.
Fernández, Esperanza, et al.. (2023). Defining a new diagnostic biomarker panel for malignant pleural mesothelioma using a novel proteomic technique.. OA1557–OA1557. 1 indexed citations
4.
Hanning, Nikita, Hannah Ceuleers, Joris G. De Man, et al.. (2022). Volatile organic compound profiling as a potential biomarker in irritable bowel syndrome: A feasibility study. Frontiers in Medicine. 9. 960000–960000. 8 indexed citations
5.
Janssens, Eline, Karim Vermaelen, Jan P. van Meerbeeck, et al.. (2022). Headspace Volatile Organic Compound Profiling of Pleural Mesothelioma and Lung Cancer Cell Lines as Translational Bridge for Breath Research. Frontiers in Oncology. 12. 851785–851785. 9 indexed citations
6.
Janssens, Eline, Jo Raskin, Veerle Surmont, et al.. (2022). External Validation of a Breath-Based Prediction Model for Malignant Pleural Mesothelioma. Cancers. 14(13). 3182–3182. 4 indexed citations
7.
Lamote, Kevin, et al.. (2021). Lung cancer screening by volume computed tomography: thriving to high performance. Breathe. 17(4). 210063–210063. 2 indexed citations
8.
Meerbeeck, Jan P. van, et al.. (2021). Clinical utility of diagnostic biomarkers in malignant pleural mesothelioma: a systematic review and meta-analysis. European Respiratory Review. 30(162). 210057–210057. 32 indexed citations
9.
Meerbeeck, Jan P. van, Erik Fransén, Jo Raskin, et al.. (2021). DNA Methylation as a Diagnostic Biomarker for Malignant Mesothelioma: A Systematic Review and Meta-Analysis. Journal of Thoracic Oncology. 16(9). 1461–1478. 21 indexed citations
10.
Winter, Benedicte Y. De, Kevin Lamote, Jan P. van Meerbeeck, et al.. (2020). A Literature Review of the Potential Diagnostic Biomarkers of Head and Neck Neoplasms. Frontiers in Oncology. 10. 1020–1020. 20 indexed citations
11.
Janssens, Eline, Jan P. van Meerbeeck, & Kevin Lamote. (2020). Volatile organic compounds in human matrices as lung cancer biomarkers: a systematic review. Critical Reviews in Oncology/Hematology. 153. 103037–103037. 70 indexed citations
12.
Lamote, Kevin, et al.. (2020). The scent of COVID-19: viral (semi-)volatiles as fast diagnostic biomarkers?. Journal of Breath Research. 14(4). 42001–42001. 58 indexed citations
13.
Winter, Benedicte Y. De, et al.. (2020). Volatomics in inflammatory bowel disease and irritable bowel syndrome. EBioMedicine. 54. 102725–102725. 29 indexed citations
14.
Geffen, Wouter H. van, Kevin Lamote, Adrien Costantini, et al.. (2019). The electronic nose: emerging biomarkers in lung cancer diagnostics. Breathe. 15(4). e135–e141. 16 indexed citations
15.
Kanellakis, Nikolaos I. & Kevin Lamote. (2019). Management of incidental nodules in lung cancer screening: ready for prime-time?. Breathe. 15(4). 346–349. 1 indexed citations
16.
Meerbeeck, Jan P. van, et al.. (2018). Breath analysis as a diagnostic and screening tool for malignant pleural mesothelioma: a systematic review. Translational Lung Cancer Research. 7(5). 520–536. 31 indexed citations
17.
Lamote, Kevin, et al.. (2017). Exhaled breath to screen for malignant pleural mesothelioma: a validation study. European Respiratory Journal. 50(6). 1700919–1700919. 34 indexed citations
18.
Lamote, Kevin, et al.. (2016). Detection of malignant pleural mesothelioma in exhaled breath by multicapillary column/ion mobility spectrometry (MCC/IMS). Journal of Breath Research. 10(4). 46001–46001. 27 indexed citations
19.
20.
Lamote, Kevin, et al.. (2014). A Breath Test for Diagnosing Malignant Pleural Mesothelioma. Annals of Oncology. 25. iv543–iv543. 4 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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