Laurent Milot
Impact in
-
- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- Hepatology top 5%
Papers in
- Hepatology 25
- Hepatocellular Carcinoma Treatment and Prognosis 21
-
- MRI in cancer diagnosis 24
- Radiomics and Machine Learning in Medical Imaging 22
- Ultrasound Imaging and Elastography 10
- Co-authors
- Peter N. BurnsRoss WilliamsMasoom A. HaiderMark FruitmanSelina SchmockerErin KennedyGina BrownRobin S. McLeod
- Journals
- European Radiology (7 papers)Radiology (5 papers)Journal of Clinical Oncology (4 papers)Journal of Vascular and Interventional Radiology (3 papers)Annals of Surgical Oncology (3 papers)
- Partner nations
- CanadaFranceUnited States
In The Last Decade
Laurent Milot
98 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 88
- Radiology, Nuclear Medicine and Imaging 944
- Hepatology 257
- Pulmonary and Respiratory Medicine 960
- Oncology 657
- Gastroenterology 111
Countries citing papers authored by Laurent Milot
This map shows the geographic impact of Laurent Milot'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 Laurent Milot with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Laurent Milot more than expected).
Fields of papers citing papers by Laurent Milot
This network shows the impact of papers produced by Laurent Milot. 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 Laurent Milot. The network helps show where Laurent Milot may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Laurent Milot, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 0 | |
| 6 | 2023 | 4 | |
| 7 | 2023 | 6 | |
| 8 | 2023 | 14 | |
| 9 | 2019 | 5 | |
| 10 | 2018 | 5 | |
| 11 | 2018 | 4 | |
| 12 | 2018 | 20 | |
| 13 | 2016 | 12 | |
| 14 | 2015 | 11 | |
| 15 | 2009 | 5 | |
| 16 | 2009 | 6 | |
| 17 | 2008 | 47 | |
| 18 | 2007 | 4 | |
| 19 | 2006 | 107 | |
| 20 | 2005 | 13 |
About Laurent Milot
Laurent Milot is a scholar working on Hepatology, Radiology, Nuclear Medicine and Imaging, Health Informatics, Pulmonary and Respiratory Medicine and Gastroenterology, having authored 105 papers that have together received 2.3k indexed citations. Recurring topics across this work include MRI in cancer diagnosis (24 papers), Radiomics and Machine Learning in Medical Imaging (22 papers), Hepatocellular Carcinoma Treatment and Prognosis (21 papers), Ultrasound and Hyperthermia Applications (14 papers), Renal cell carcinoma treatment (12 papers), Prostate Cancer Diagnosis and Treatment (10 papers), Ultrasound Imaging and Elastography (10 papers) and Neuroendocrine Tumor Research Advances (9 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (944 citations), Hepatology (257 citations), Pulmonary and Respiratory Medicine (960 citations), Oncology (657 citations) and Gastroenterology (111 citations). Laurent Milot has collaborated with scholars based in Canada, France and United States. Frequent co-authors include Peter N. Burns, Ross Williams, Masoom A. Haider, Mark Fruitman, Selina Schmocker, Erin Kennedy, Gina Brown, Robin S. McLeod, Eisar Al‐Sukhni and John M. Hudson. Their work appears in journals such as European Radiology, Radiology, Journal of Clinical Oncology, Journal of Vascular and Interventional Radiology and Annals of Surgical Oncology.
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.