Connie E. Kim
Impact in
- Neurology top 10%
- Neurological disorders and treatments
Papers in
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- Nuclear Structure and Function 2
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- Medical Imaging Techniques and Applications 2
- Radiomics and Machine Learning in Medical Imaging 2
- Ultrasound Imaging and Elastography 1
- Co-authors
- William T. Dauer (3 shared papers)Ashirbani Saha (3 shared papers)Lauren M. Tanabe (1 shared paper)Noga Alagem (1 shared paper)Maciej A. Mazurowski (3 shared papers)Lars J. Grimm (3 shared papers)Sujata V. Ghate (2 shared papers)Ruth Walsh (3 shared papers)
- Journals
- Nature Reviews Neurology (1 paper)British Journal of Cancer (1 paper)Cancers (1 paper)Journal of Magnetic Resonance Imaging (1 paper)American Journal Of Pathology (1 paper)
- Partner nations
- United StatesPortugalCanada
In The Last Decade
Connie E. Kim
9 papers receiving 579 citations
Peers
Comparison fields: 5 of 66
- Neurology 138
- Health Informatics 11
- Radiology, Nuclear Medicine and Imaging 186
- Cellular and Molecular Neuroscience 122
- Artificial Intelligence 130
Countries citing papers authored by Connie E. Kim
This map shows the geographic impact of Connie E. Kim'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 Connie E. Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Connie E. Kim more than expected).
Fields of papers citing papers by Connie E. Kim
This network shows the impact of papers produced by Connie E. Kim. 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 Connie E. Kim. The network helps show where Connie E. Kim may publish in the future.
Co-authors
The 25 scholars most cited alongside Connie E. Kim, 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 | 2018 | 187 | |
| 2 | 2009 | 119 | |
| 3 | 2004 | 111 | |
| 4 | 2010 | 110 | |
| 5 | 2019 | 26 | |
| 6 | 2013 | 22 | |
| 7 | 2011 | 8 | |
| 8 | 2003 | 3 | |
| 9 | 2012 | 2 | |
| 10 | 2018 | 0 |
About Connie E. Kim
Connie E. Kim is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging, Cellular and Molecular Neuroscience, Neurology and Oncology, having authored 10 papers that have together received 588 indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (2 papers), Nuclear Structure and Function (2 papers), AI in cancer detection (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Neurological disorders and treatments (2 papers), Genetic Neurodegenerative Diseases (2 papers), Hereditary Neurological Disorders (1 paper) and Ultrasound Imaging and Elastography (1 paper). The work is most often cited by research in Neurology (138 citations), Health Informatics (11 citations), Radiology, Nuclear Medicine and Imaging (186 citations), Cellular and Molecular Neuroscience (122 citations) and Artificial Intelligence (130 citations). Connie E. Kim has collaborated with scholars based in United States, Portugal and Canada. Frequent co-authors include William T. Dauer, Ashirbani Saha, Lauren M. Tanabe, Noga Alagem, Maciej A. Mazurowski, Lars J. Grimm, Sujata V. Ghate, Ruth Walsh, Michael R. Harowicz and Guy Perkins. Their work appears in journals such as Nature Reviews Neurology, British Journal of Cancer, Cancers, Journal of Magnetic Resonance Imaging and American Journal Of Pathology.
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.