Mengdie Yuan

725 citations
10 papers · 455 indexed · 1 hit paper · h-index 5
Topics
Statistical Methods and Inference (3 papers)Statistical Methods in Clinical Trials (3 papers)Statistical Methods and Bayesian Inference (2 papers)
Partner nations
United StatesChina

In The Last Decade

Mengdie Yuan

10 papers receiving 451 citations

Hit Papers

FDA Approval Summary: Pembrolizumab for the Treatment of ...20212026202220242021100200300

Peers

Mengdie Yuan
Comparison fields: 5 of 60
  • Oncology 308
  • Pulmonary and Respiratory Medicine 146
  • Cancer Research 131
  • Immunology 78
  • Molecular Biology 76
Replace Marco Imperatori with:
Marco Imperatori Italy
Christoph Heining Germany
Ashish Sangal United States
Zhen-Hai Lu China
Linda Mahjoubi France
Simona Aloe Italy
María Luisa Limón Spain
Deirdre Kelly Canada
Guoqiang Wang China
Dilara Akhoundova Switzerland
Mengdie Yuan relative to Marco Imperatori Italy Marco Imperatori's profile →
Citations per field
00.5×8.6×
Marco Imperatori · 1×
Citations per year

Countries citing papers authored by Mengdie Yuan

Since Specialization
Citations

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

Fields of papers citing papers by Mengdie Yuan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mengdie Yuan

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

All Works

10 of 10 papers shown
#WorkIndexed citations
1 7
2 21
3 77
4
FDA Approval Summary: Pembrolizumab for the Treatment of Tumor Mutational Burden–High Solid Tumorsbreakdown →
330
5 4
6 6
7 2
8 3
9 1
10 4

About Mengdie Yuan

Mengdie Yuan is a scholar working on Statistics and Probability, Oncology and Hepatology, having authored 10 papers that have together received 455 indexed citations. Recurring topics across this work include Statistical Methods and Inference (3 papers), Statistical Methods in Clinical Trials (3 papers) and Statistical Methods and Bayesian Inference (2 papers). The work is most often cited by research in Oncology (308 citations), Cancer Research (131 citations) and Hepatology (37 citations). Mengdie Yuan has collaborated with scholars based in United States and China. Frequent co-authors include Steven J. Lemery, Lola A. Fashoyin‐Aje, Richard Pazdur, Martha Donoghue, Lisa Rodríguez, Marc R. Theoret, Julia A. Beaver, Soma Ghosh, Leigh Marcus and Reena Philip. Their work appears in journals such as Clinical Cancer Research, Statistics in Medicine and The Oncologist.

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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