Michelle Guo

1.2k citations
9 papers · 168 · h-index 6

Impact in

Papers in

Michelle Guo

7 papers receiving 162 citations

Peers

Michelle Guo
Comparison fields: 5 of 86
  • Health Informatics 20
  • General Dentistry 7
  • Computer Vision and Pattern Recognition 42
  • Medical Laboratory Technology 3
  • Critical Care and Intensive Care Medicine 10
Replace Fabio Stroppa with:
Fabio Stroppa Türkiye
DM Anisuzzaman United States
Mohammad Khaleel Sallam Ma’aitah Cyprus
Behrouz Rostami United States
Yujia Xu United Kingdom
Amir H. Abdi Canada
Tae Young Kim South Korea
Muhammad Iftikhar Pakistan
Darko Katić Germany
Justin Sutherland Canada
Michelle Guo relative to Fabio Stroppa Türkiye Fabio Stroppa's profile →
Citations per field
00.5×3.1×
Fabio Stroppa · 1×
Citations per year

Countries citing papers authored by Michelle Guo

Since Specialization
Citations

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

Fields of papers citing papers by Michelle Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1 201978
2 202038
3 202319
4 201917
5
Towards Vision-Based Smart Hospitals: A System for Tracking and Monitoring Hand Hygiene Compliance
20177
6
3D Point Cloud-Based Visual Prediction of ICU Mobility Care Activities.
20185
7 20204
8
The Frequency of Lithium-Rich Giants in Globular Clusters
20160
9 20240

About Michelle Guo

Michelle Guo is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Computational Mechanics, Infectious Diseases and Critical Care and Intensive Care Medicine, having authored 9 papers that have together received 168 indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (2 papers), Robot Manipulation and Learning (2 papers), Historical Geography and Cartography (1 paper), Infection Control in Healthcare (1 paper), Video Surveillance and Tracking Methods (1 paper), Image Processing and 3D Reconstruction (1 paper), Crystal Structures and Properties (1 paper) and Intensive Care Unit Cognitive Disorders (1 paper). The work is most often cited by research in Health Informatics (20 citations), General Dentistry (7 citations), Computer Vision and Pattern Recognition (42 citations), Medical Laboratory Technology (3 citations) and Critical Care and Intensive Care Medicine (10 citations). Michelle Guo has collaborated with scholars based in United States and Switzerland. Frequent co-authors include Li Fei-Fei, William Beninati, Serena Yeung, Arnold Milstein, Alexandre Alahi, Albert Haque, N. Lance Downing, Kayla Deru, Jeffrey K. Jopling and Bingbin Liu. Their work appears in journals such as IEEE Robotics and Automation Letters, Journal of the American Medical Informatics Association, npj Digital Medicine, Infoscience (Ecole Polytechnique Fédérale de Lausanne) and AAS.

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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