Manway Liu

16.2k citations
14 papers · 1.8k indexed · 2 hit papers · h-index 12
Topics
Adipose Tissue and Metabolism (4 papers)PI3K/AKT/mTOR signaling in cancer (3 papers)Advanced Breast Cancer Therapies (2 papers)

In The Last Decade

Manway Liu

14 papers receiving 1.8k citations

Hit Papers

Variable generalization performance of a deep learning mo...201420262018202220182014250500750

Peers

Manway Liu
Comparison fields: 5 of 137
  • Molecular Biology 607
  • Radiology, Nuclear Medicine and Imaging 458
  • Pulmonary and Respiratory Medicine 406
  • Artificial Intelligence 358
  • Oncology 339
Replace Sebastian Foersch with:
Sebastian Foersch Germany
Eoin McKinney United Kingdom
Phedias Diamandis Canada
Lisa C. Adams Germany
Clare Verrill United Kingdom
Gigin Lin Taiwan
Alexis B. Carter United States
Aikaterini Kotrotsou United States
Jeremy R. Glissen Brown United States
Pooja Rao United States
Manway Liu relative to Sebastian Foersch Germany Sebastian Foersch's profile →
Citations per field
00.5×1.7×
Sebastian Foersch · 1×
Citations per year

Countries citing papers authored by Manway Liu

Since Specialization
Citations

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

Fields of papers citing papers by Manway Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Manway Liu

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

All Works

14 of 14 papers shown
#WorkIndexed citations
1 21
2 1
3
Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: A cross-sectional studybreakdown →
826
4 4
5 118
6 60
7
CDK 4/6 Inhibitors Sensitize PIK3CA Mutant Breast Cancer to PI3K Inhibitorsbreakdown →
351
8 56
9 35
10 21
11 81
12 60
13 69
14 132

About Manway Liu

Manway Liu is a scholar working on Physiology, Molecular Biology and Obstetrics and Gynecology, having authored 14 papers that have together received 1.8k indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (4 papers), PI3K/AKT/mTOR signaling in cancer (3 papers) and Advanced Breast Cancer Therapies (2 papers). The work is most often cited by research in Health Informatics (249 citations), Radiology, Nuclear Medicine and Imaging (458 citations) and Oncology (339 citations). Manway Liu has collaborated with scholars based in United States, Switzerland and Spain. Frequent co-authors include J. Titano, Marcus A. Badgeley, Eric K. Oermann, Anthony Costa, John R. Zech, Simon Kasif, Alan Huang, Robert Schlegel, Joseph Lehár and Arthur Liberzon. Their work appears in journals such as Bioinformatics, Cancer Cell and Cancer Research.

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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