Lisha Lu

25 papers receiving 498 citations

Peers

Lisha Lu
Comparison fields: 5 of 94
  • Pathology and Forensic Medicine 69
  • Cellular and Molecular Neuroscience 71
  • Oncology 85
  • Molecular Biology 199
  • Immunology 50
Replace Siyang Zhang with:
Siyang Zhang China
Chengzhong Lin China
Patrick Allison United States
Guillermo Izquierdo United Kingdom
Zhenwei Zhao China
Jinlong Liu China
Maria A. Hahn United States
Elaine Guo Yan Chew Singapore
Guojun Wei China
Barbara Bogner Austria
Lisha Lu relative to Siyang Zhang China Siyang Zhang's profile →
Citations per field
00.5×1.5×
Siyang Zhang · 1×
Citations per year

Countries citing papers authored by Lisha Lu

Since Specialization
Citations

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

Fields of papers citing papers by Lisha Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200075
2 201564
3 199755
4 201443
5 202437
6 201936
7 201627
8 202321
9 201420
10 202218
11 202017
12
Pre-operative TNM staging of primary colorectal cancer by (18)F-FDG PET-CT or PET: a meta-analysis including 2283 patients.
201517
13 202212
14 201612
15 201511
16 201811
17 20139
18 20136
19 20252
20 20182

About Lisha Lu

Lisha Lu is a scholar working on Molecular Biology, Pathology and Forensic Medicine, Surgery, Oncology and Electrical and Electronic Engineering, having authored 27 papers that have together received 501 indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (3 papers), Advanced Battery Technologies Research (2 papers), Pluripotent Stem Cells Research (2 papers), Total Knee Arthroplasty Outcomes (2 papers), Advanced Battery Materials and Technologies (2 papers), Epigenetics and DNA Methylation (2 papers), Advanced battery technologies research (2 papers) and Immune Response and Inflammation (2 papers). The work is most often cited by research in Pathology and Forensic Medicine (69 citations), Cellular and Molecular Neuroscience (71 citations), Oncology (85 citations), Molecular Biology (199 citations) and Immunology (50 citations). Lisha Lu has collaborated with scholars based in China, United States and Iran. Frequent co-authors include Gregg D. Stanwood, Paul McGonigle, Zhaoming Li, Zhi‐Yuan Zhou, Jiumao Lin, Heithem M. El‐Hodiri, Wujin Chen, Theodore G. Wensel, Kevin C. Slep and Melvin I. Simon. Their work appears in journals such as Annals of Hematology, PROTEOMICS - CLINICAL APPLICATIONS, Journal of Biomedical Nanotechnology, Energy storage materials and Biochemical and Biophysical Research Communications.

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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