Cynthia Yang

616 total citations
10 papers, 234 citations indexed

About

Cynthia Yang is a scholar working on Artificial Intelligence, Health Informatics and Epidemiology. According to data from OpenAlex, Cynthia Yang has authored 10 papers receiving a total of 234 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 2 papers in Health Informatics and 2 papers in Epidemiology. Recurrent topics in Cynthia Yang's work include Machine Learning in Healthcare (6 papers), Meta-analysis and systematic reviews (2 papers) and Intellectual Property and Patents (2 papers). Cynthia Yang is often cited by papers focused on Machine Learning in Healthcare (6 papers), Meta-analysis and systematic reviews (2 papers) and Intellectual Property and Patents (2 papers). Cynthia Yang collaborates with scholars based in Netherlands, United States and South Korea. Cynthia Yang's co-authors include Thomas Klose, Yunyun Yang, Peter R. Rijnbeek, Jan A. Kors, Egill A. Friðgeirsson, Jenna Reps, Luis H. John, Aniek F. Markus, Ross D. Williams and Maria de Ridder and has published in prestigious journals such as Journal of the American Medical Informatics Association, Computer Methods and Programs in Biomedicine and Journal Of Big Data.

In The Last Decade

Cynthia Yang

10 papers receiving 223 citations

Peers

Cynthia Yang

AI

MTI

HIM

EPIDE

EE

Kornelia Batko Poland

Ståle Walderhaug Norway

Yesha Raval United States

Frédérique Segond France

Matthias Schulte‐Althoff Germany

Rob J. B. Vanwersch Netherlands

Leying Guan United States

Rubén A. Proaño United States

Birgit Brigl Germany

Bernard Gouget France

Kornelia Batko Poland

Cynthia Yang

58 ×0.6

AI

9 ×0.2

MTI

55 ×1.6

HIM

11 ×0.4

EPIDE

14 ×0.7

EE

Citations per year, relative to Cynthia Yang Cynthia Yang (= 1×) peers Kornelia Batko

Countries citing papers authored by Cynthia Yang

Since Specialization

Citations

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

Fields of papers citing papers by Cynthia Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cynthia Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Cynthia Yang. A scholar is included among the top collaborators of Cynthia Yang 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 Cynthia Yang. Cynthia Yang 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

1.

Yang, Cynthia, Egill A. Friðgeirsson, Jan A. Kors, Jenna Reps, & Peter R. Rijnbeek. (2024). Impact of random oversampling and random undersampling on the performance of prediction models developed using observational health data. Journal Of Big Data. 11(1). 30 indexed citations

2.

Yang, Cynthia, Egill A. Friðgeirsson, Jan A. Kors, et al.. (2023). Does Using a Stacking Ensemble Method to Combine Multiple Base Learners Within a Database Improve Model Transportability?. Studies in health technology and informatics. 302. 129–130. 2 indexed citations

3.

Friðgeirsson, Egill A., Luis H. John, Jan A. Kors, et al.. (2022). Use of unstructured text in prognostic clinical prediction models: a systematic review. medRxiv. 2 indexed citations

4.

Yang, Cynthia, Jan A. Kors, Luis H. John, et al.. (2022). Trends in the conduct and reporting of clinical prediction model development and validation: a systematic review. Journal of the American Medical Informatics Association. 29(5). 983–989. 39 indexed citations

5.

Friðgeirsson, Egill A., Luis H. John, Jan A. Kors, et al.. (2022). Use of unstructured text in prognostic clinical prediction models: a systematic review. Journal of the American Medical Informatics Association. 29(7). 1292–1302. 37 indexed citations

6.

Khalid, Sara, Cynthia Yang, Clair Blacketer, et al.. (2021). A standardized analytics pipeline for reliable and rapid development and validation of prediction models using observational health data. Computer Methods and Programs in Biomedicine. 211. 106394–106394. 25 indexed citations

7.

Yang, Cynthia, Jan A. Kors, Luis H. John, et al.. (2021). Trends in the conduct and reporting of clinical prediction model development and validation: a systematic review. medRxiv. 3 indexed citations

8.

Yang, Cynthia, et al.. (2010). Enhancing patent landscape analysis with visualization output. World Patent Information. 32(3). 203–220. 26 indexed citations

9.

Cameron, Rebecca P., et al.. (2008). The Transcultural Wellness Center: Rehabilitation and Recovery in Asian and Pacific Islander Mental Health Care. Journal of Social Work in Disability & Rehabilitation. 7(3-4). 284–314. 1 indexed citations

10.

Yang, Yunyun, et al.. (2008). Text mining and visualization tools – Impressions of emerging capabilities. World Patent Information. 30(4). 280–293. 69 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