Connie E. Kim

824 total citations
10 papers, 588 citations indexed

About

Connie E. Kim is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Cellular and Molecular Neuroscience. According to data from OpenAlex, Connie E. Kim has authored 10 papers receiving a total of 588 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 5 papers in Radiology, Nuclear Medicine and Imaging and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Connie E. Kim's work include Radiomics and Machine Learning in Medical Imaging (2 papers), Medical Imaging Techniques and Applications (2 papers) and AI in cancer detection (2 papers). Connie E. Kim is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (2 papers), Medical Imaging Techniques and Applications (2 papers) and AI in cancer detection (2 papers). Connie E. Kim collaborates with scholars based in United States, Portugal and Canada. Connie E. Kim's co-authors include William T. Dauer, Maciej A. Mazurowski, Noga Alagem, Lars J. Grimm, Ashirbani Saha, Lauren M. Tanabe, Michael R. Harowicz, Sujata V. Ghate, Ruth Walsh and Mark H. Ellisman and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and American Journal Of Pathology.

In The Last Decade

Connie E. Kim

9 papers receiving 579 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Connie E. Kim United States	7	232	186	138	130	122	10	588
Fei Xiong China	11	91 0.4×	307 1.7×	63 0.5×	51 0.4×	71 0.6×	27	595
Karra A. Jones United States	16	118 0.5×	209 1.1×	86 0.6×	28 0.2×	37 0.3×	37	624
Kim Lemmens Belgium	13	169 0.7×	44 0.2×	34 0.2×	34 0.3×	145 1.2×	19	516
Minwei Zhu China	15	167 0.7×	67 0.4×	79 0.6×	26 0.2×	65 0.5×	33	469
Parth Shah United States	12	330 1.4×	46 0.2×	90 0.7×	9 0.1×	134 1.1×	29	706
Mário João Fartaria Switzerland	14	93 0.4×	229 1.2×	100 0.7×	35 0.3×	23 0.2×	26	568
Katherine Holland‐Bouley United States	11	190 0.8×	37 0.2×	48 0.3×	56 0.4×	130 1.1×	17	836
Courtney Thaxton United States	15	388 1.7×	35 0.2×	152 1.1×	23 0.2×	309 2.5×	21	1.0k
Michael Cheng United States	12	178 0.8×	86 0.5×	13 0.1×	85 0.7×	107 0.9×	25	514
Marc Ingenwerth Germany	18	206 0.9×	248 1.3×	18 0.1×	38 0.3×	24 0.2×	36	652

Countries citing papers authored by Connie E. Kim

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Connie E. Kim

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

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

Saha, Ashirbani, Lars J. Grimm, Sujata V. Ghate, et al.. (2019). Machine learning‐based prediction of future breast cancer using algorithmically measured background parenchymal enhancement on high‐risk screening MRI. Journal of Magnetic Resonance Imaging. 50(2). 456–464. 26 indexed citations

Saha, Ashirbani, Michael R. Harowicz, Lars J. Grimm, et al.. (2018). A machine learning approach to radiogenomics of breast cancer: a study of 922 subjects and 529 DCE-MRI features. British Journal of Cancer. 119(4). 508–516. 187 indexed citations

Saha, Ashirbani, Michael R. Harowicz, Lars J. Grimm, et al.. (2018). Association of high proliferation marker Ki-67 expression with DCEMR imaging features of breast: a large scale evaluation. 15. 6–6.

Santos, Mariana, Sandra Rebelo, Paula J. M. van Kleeff, et al.. (2013). The Nuclear Envelope Protein, LAP1B, Is a Novel Protein Phosphatase 1 Substrate. PLoS ONE. 8(10). e76788–e76788. 22 indexed citations

Ghate, Sujata V., et al.. (2012). Using the BI-RADS Lexicon in a Restrictive Form of Double Reading as a Strategy for Minimizing Screening Mammography Recall Rates. American Journal of Roentgenology. 198(4). 962–970. 2 indexed citations

Kim, Connie E., Kam-Meng Tchou-Wong, & William N. Rom. (2011). Sputum-Based Molecular Biomarkers for the Early Detection of Lung Cancer: Limitations and Promise. Cancers. 3(3). 2975–2989. 8 indexed citations

Kim, Connie E., Álex Pérez, Guy Perkins, Mark H. Ellisman, & William T. Dauer. (2010). A molecular mechanism underlying the neural-specific defect in torsinA mutant mice. Proceedings of the National Academy of Sciences. 107(21). 9861–9866. 110 indexed citations

Tanabe, Lauren M., Connie E. Kim, Noga Alagem, & William T. Dauer. (2009). Primary dystonia: molecules and mechanisms. Nature Reviews Neurology. 5(11). 598–609. 119 indexed citations

Li, Chi-Ming, Connie E. Kim, Jimmy Zhu, et al.. (2004). CTNNB1 Mutations and Overexpression of Wnt/β-Catenin Target Genes in WT1-Mutant Wilms' Tumors. American Journal Of Pathology. 165(6). 1943–1953. 111 indexed citations

10.

Kim, Connie E., et al.. (2003). Fortuitous Detection of Papillary Carcinoma of the Thyroid With F-18 FDG Positron Emission Tomography in a Patient With Non-Hodgkin Lymphoma. Clinical Nuclear Medicine. 28(9). 782–783. 3 indexed citations

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.

Explore authors with similar magnitude of impact