Laila Poisson

28.4k citations
108 papers · 3.6k indexed · 1 hit paper · h-index 32

Laila Poisson

106 papers receiving 3.5k citations

Hit Papers

Deep-Learning Convolutional Neural Networks Accurately Cl...3252018202620202023100200300

Peers

Laila Poisson
Comparison fields: 5 of 146
  • Genetics 1.0k
  • Cancer Research 881
  • Health Informatics 55
  • Radiology, Nuclear Medicine and Imaging 917
  • Biophysics 199
Replace Sunit Das with:
Sunit Das Canada
Daniela A. Bota United States
Nirav Patil United States
Gelareh Zadeh Canada
Ashish H. Shah United States
Michael D. Jenkinson United Kingdom
Raymond Y. Huang United States
Joshua D. Bernstock United States
Kyle M. Walsh United States
Suzanne Z. Powell United States
Laila Poisson relative to Sunit Das Canada Sunit Das's profile →
Citations per field
00.5×2.9×
Sunit Das · 1×
Citations per year

Countries citing papers authored by Laila Poisson

Since Specialization
Citations

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

Fields of papers citing papers by Laila Poisson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Laila Poisson, 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 Laila Poisson Line = papers co-authored together Laila Poisson links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20244
4 20241
5 20243
6 20234
7 202242
8 202212
9 20225
10 20227
11 20223
12 202114
13 202150
14 20218
15 202011
16 20198
17 201818
18 20189
19 2017283
20 2003101

About Laila Poisson

Laila Poisson is a scholar working on Genetics, Cancer Research and Health Informatics, having authored 108 papers that have together received 3.6k indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (20 papers), Radiomics and Machine Learning in Medical Imaging (14 papers), MicroRNA in disease regulation (11 papers), COVID-19 Clinical Research Studies (10 papers), Cancer-related molecular mechanisms research (7 papers), COVID-19 and healthcare impacts (6 papers), Molecular Biology Techniques and Applications (6 papers) and Metabolomics and Mass Spectrometry Studies (5 papers). The work is most often cited by research in Genetics (1.0k citations), Cancer Research (881 citations) and Health Informatics (55 citations). Laila Poisson has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Tom Mikkelsen, Rajan Jain, Lonni Schultz, Chaya Brodie, Simona Cazacu, Cunli Xiang, Benjamin A. Rybicki, Mary Maliarik, Debashis Ghosh and Ana C. deCarvalho. Their work appears in journals such as Neuro-Oncology, Oncotarget, American Journal of Neuroradiology, Journal of Neuro-Oncology and Cancers.

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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