Michael Pekala
- Radiology, Nuclear Medicine and Imaging top 5%
- Ophthalmology top 2%
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence top 10%
- Molecular Biology
- Co-authors
- Kátia D. PachecoPhilippe BurlinaNeil M. BresslerNeil JoshiDavid FreundWojciech CzajaI-Jeng WangGregory D. Hager
- Topics
- Retinal and Optic Conditions (3 papers)Retinal Imaging and Analysis (3 papers)Distributed systems and fault tolerance (2 papers)
- Partner nations
- United States
In The Last Decade
Michael Pekala
15 papers receiving 562 citations
Hit Papers
Peers
Comparison fields: 5 of 78
- Radiology, Nuclear Medicine and Imaging 406
- Ophthalmology 334
- Computer Vision and Pattern Recognition 112
- Artificial Intelligence 103
- Molecular Biology 41
Countries citing papers authored by Michael Pekala
This map shows the geographic impact of Michael Pekala'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 Pekala with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Pekala more than expected).
Fields of papers citing papers by Michael Pekala
This network shows the impact of papers produced by Michael Pekala. 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 Pekala. The network helps show where Michael Pekala may publish in the future.
Co-authorship network of co-authors of Michael Pekala
This figure shows the co-authorship network connecting the top 25 collaborators of Michael Pekala. A scholar is included among the top collaborators of Michael Pekala 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 Michael Pekala. Michael Pekala is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 9 | |
| 3 | 4 | |
| 4 | 66 | |
| 5 | Automated Grading of Age-Related Macular Degeneration From Color Fundus Images Using Deep Convolutional Neural Networksbreakdown → | 426 |
| 6 | 12 | |
| 7 | 10 | |
| 8 | 10 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | 2 | |
| 12 | 7 | |
| 13 | 8 | |
| 14 | 1 | |
| 15 | 8 | |
| 16 | Model-Based Autonomy for the Next Generation of Robotic Spacecraft | 10 |
About Michael Pekala
Michael Pekala is a scholar working on Software, Ophthalmology and Hardware and Architecture, having authored 16 papers that have together received 575 indexed citations. Recurring topics across this work include Retinal and Optic Conditions (3 papers), Retinal Imaging and Analysis (3 papers) and Distributed systems and fault tolerance (2 papers). The work is most often cited by research in Ophthalmology (334 citations), Health Informatics (25 citations) and Radiology, Nuclear Medicine and Imaging (406 citations). Michael Pekala has collaborated with scholars based in United States. Frequent co-authors include Kátia D. Pacheco, Philippe Burlina, Neil M. Bressler, Neil Joshi, David Freund, Wojciech Czaja, I-Jeng Wang, Gregory D. Hager, Brian C. Williams and R. Jacob Vogelstein. Their work appears in journals such as The Journal of Physical Chemistry C, Lecture notes in computer science and JAMA Ophthalmology.
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.