Michael W. Lu
- Oncology top 0.5%
- HER2/EGFR in Cancer Research 8
- Cancer Treatment and Pharmacology 4
- Peptidase Inhibition and Analysis 2
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- Monoclonal and Polyclonal Antibodies Research 4
- Cancer Research top 5%
- Cancer Genomics and Diagnostics 4
- Health Informatics top 5%
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- Lung Cancer Treatments and Mutations 5
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- Statistical Methods in Clinical Trials 3
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- Clinical practice guidelines implementation 1
- Co-authors
- Ian E. KropEllie GuardinoDo‐Youn OhLuca GianniVéronique DièrasSteven R. OlsenMark D. PegramSunil Verma
- Partner nations
- United StatesSwitzerlandFrance
In The Last Decade
Michael W. Lu
18 papers receiving 3.6k citations
Hit Papers
Peers
Comparison fields: 5 of 106
- Oncology 2.9k
- Radiology, Nuclear Medicine and Imaging 1.6k
- Cancer Research 530
- Health Informatics 44
- Pulmonary and Respiratory Medicine 1.0k
Countries citing papers authored by Michael W. Lu
This map shows the geographic impact of Michael W. 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 Michael W. Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael W. Lu more than expected).
Fields of papers citing papers by Michael W. Lu
This network shows the impact of papers produced by Michael W. 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 Michael W. Lu. The network helps show where Michael W. Lu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Michael W. Lu, 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 | 2023 | 1 | |
| 2 | 2022 | 13 | |
| 3 | Evaluating eligibility criteria of oncology trials using real-world data and AIbreakdown → | 2021 | 184 |
| 4 | 2020 | 2 | |
| 5 | 2019 | 72 | |
| 6 | 2019 | 1 | |
| 7 | 2018 | 1 | |
| 8 | 2018 | 173 | |
| 9 | 2017 | 25 | |
| 10 | 2016 | 14 | |
| 11 | Trastuzumab Emtansine for HER2-Positive Advanced Breast Cancerbreakdown → | 2012 | 2665 |
| 12 | 2012 | 274 | |
| 13 | 2012 | 74 | |
| 14 | 2012 | 66 | |
| 15 | 2012 | 29 | |
| 16 | 2012 | 56 | |
| 17 | 2010 | 13 | |
| 18 | 2008 | 20 |
About Michael W. Lu
Michael W. Lu is a scholar working on Statistics and Probability, Oncology, Cancer Research, Radiology, Nuclear Medicine and Imaging and Pharmacy, having authored 18 papers that have together received 3.7k indexed citations. Recurring topics across this work include HER2/EGFR in Cancer Research (8 papers), Lung Cancer Treatments and Mutations (5 papers), Cancer Genomics and Diagnostics (4 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), Cancer Treatment and Pharmacology (4 papers), Statistical Methods in Clinical Trials (3 papers), Peptidase Inhibition and Analysis (2 papers) and Clinical practice guidelines implementation (1 paper). The work is most often cited by research in Oncology (2.9k citations), Radiology, Nuclear Medicine and Imaging (1.6k citations), Cancer Research (530 citations), Health Informatics (44 citations) and Pulmonary and Respiratory Medicine (1.0k citations). Michael W. Lu has collaborated with scholars based in United States, Switzerland and France. Frequent co-authors include Ian E. Krop, Ellie Guardino, Do‐Youn Oh, Luca Gianni, Véronique Dièras, Steven R. Olsen, Mark D. Pegram, Sunil Verma, David Miles and Fang Ting Liang. Their work appears in journals such as Journal of Clinical Oncology, Clinical Cancer Research, Cancer, Technology in Cancer Research & Treatment and New England Journal of Medicine.
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.