Wei Mu

4.8k citations
91 papers · 2.9k · 2 hit papers · h-index 26

Impact in

Papers in

Wei Mu

84 papers receiving 2.9k citations

Wei Mu's Hit Papers

Non-invasive measurement of PD-L1 status and prediction of immunotherapy response using deep learning of PET/CT images 2021 · 156 citations
1560+2+4Years since publication100200300

Peers

Wei Mu
Comparison fields: 5 of 127
  • Radiology, Nuclear Medicine and Imaging 1.0k
  • Health Informatics 58
  • Oncology 1.0k
  • Immunology 273
  • Pulmonary and Respiratory Medicine 359
Replace Sun Mi Kim with:
Sun Mi Kim South Korea
Katherine A. Vallis United Kingdom
Jie Tian China
Qianqian Ni China
M. Lewin France
Tristan Barrett United Kingdom
Le‐Hang Guo China
Michael T. Spiotto United States
Ming Kuang China
Luitpold Distel Germany
Wei Mu relative to Sun Mi Kim South Korea Sun Mi Kim's profile →
Citations per field
00.5×6.5×
Sun Mi Kim · 1×
Citations per year

Countries citing papers authored by Wei Mu

Since Specialization
Citations

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

Fields of papers citing papers by Wei Mu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 91 papers — load more, or switch the sort, to bring in the rest.

#Work
1
TGF-β inhibition via CRISPR promotes the long-term efficacy of CAR T cells against solid tumors
Hit paper breakdown →
2020304
2 2020247
3 2017193
4 2020192
5
Non-invasive measurement of PD-L1 status and prediction of immunotherapy response using deep learning of PET/CT images
Hit paper breakdown →
2021156
6 2018152
7 2019138
8 2021137
9 2020115
10 201976
11 202070
12 201570
13 202268
14 201958
15 201956
16 202453
17 202147
18 202141
19 202238
20 201937

About Wei Mu

Wei Mu is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, Oncology, Molecular Biology and Electrical and Electronic Engineering, having authored 91 papers that have together received 2.9k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (21 papers), CAR-T cell therapy research (16 papers), Nanowire Synthesis and Applications (7 papers), Medical Imaging Techniques and Applications (7 papers), Lung Cancer Diagnosis and Treatment (6 papers), Photoreceptor and optogenetics research (5 papers), Medical Image Segmentation Techniques (4 papers) and Hepatocellular Carcinoma Treatment and Prognosis (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (1.0k citations), Health Informatics (58 citations), Oncology (1.0k citations), Immunology (273 citations) and Pulmonary and Respiratory Medicine (359 citations). Wei Mu has collaborated with scholars based in China, United States and Sweden. Frequent co-authors include Robert J. Gillies, Xiaojun Han, Matthew B. Schabath, Jie Tian, Ilke Tunali, Haoyi Wang, Na Li, Xingying Zhang, Haolong Lin and Jianfeng Zhou. Their work appears in journals such as Blood, Frontiers in Immunology, Theranostics, IEEE Transactions on Biomedical Engineering and Nature 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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