Chung‐Feng Liu

814 total citations
44 papers, 475 citations indexed

About

Chung‐Feng Liu is a scholar working on Epidemiology, Artificial Intelligence and Health Informatics. According to data from OpenAlex, Chung‐Feng Liu has authored 44 papers receiving a total of 475 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Epidemiology, 11 papers in Artificial Intelligence and 9 papers in Health Informatics. Recurrent topics in Chung‐Feng Liu's work include Machine Learning in Healthcare (10 papers), Artificial Intelligence in Healthcare and Education (9 papers) and Sepsis Diagnosis and Treatment (8 papers). Chung‐Feng Liu is often cited by papers focused on Machine Learning in Healthcare (10 papers), Artificial Intelligence in Healthcare and Education (9 papers) and Sepsis Diagnosis and Treatment (8 papers). Chung‐Feng Liu collaborates with scholars based in Taiwan, France and Belgium. Chung‐Feng Liu's co-authors include Chia‐Jung Chen, Jhi‐Joung Wang, Zhih‐Cherng Chen, Chien‐Cheng Huang, Hung‐Jung Lin, Chien‐Chin Hsu, Kuang‐Ming Liao, Hsin‐Ginn Hwang, Yuting Shen and Chin‐Ming Chen and has published in prestigious journals such as PLoS ONE, International Journal of Environmental Research and Public Health and Medicine.

In The Last Decade

Chung‐Feng Liu

40 papers receiving 464 citations

Peers

Chung‐Feng Liu

RNMI

EPIDE

PRM

Marshall Nichols United States

Tom Lawton United Kingdom

Gina Barnes United States

Armando Bedoya United States

Fawad Qureshi United States

Jeremy A. Balch United States

Martin Seneviratne United States

Nancy Gentry United States

Martin Sepulveda United States

Marta Fernandes United States

Marshall Nichols United States

Chung‐Feng Liu

155 ×1.1

201 ×1.7

69 ×0.8

RNMI

186 ×2.3

EPIDE

46 ×0.6

PRM

Citations per year, relative to Chung‐Feng Liu Chung‐Feng Liu (= 1×) peers Marshall Nichols

Countries citing papers authored by Chung‐Feng Liu

Since Specialization

Citations

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

Fields of papers citing papers by Chung‐Feng Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chung‐Feng Liu. 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 Chung‐Feng Liu. The network helps show where Chung‐Feng Liu may publish in the future.

Co-authorship network of co-authors of Chung‐Feng Liu

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

All Works

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20 of 20 papers shown

Huang, Chien‐Cheng, Chung‐Feng Liu, Chien-Chin Hsu, et al.. (2025). Utilizing machine learning for predicting mortality in patients with heat-related illness who visited the emergency department. International Journal of Medical Informatics. 201. 105951–105951.

Nguyen, Phung‐Anh, Chien‐Cheng Huang, Chung‐Feng Liu, et al.. (2024). Acute myocardial infarction risk prediction in emergency chest pain patients: An external validation study. International Journal of Medical Informatics. 193. 105683–105683. 1 indexed citations

Liu, Mei‐Yuan, et al.. (2024). Machine Learning to Predict the Risk of Malnutrition in Hospitalized Patients with Pneumonia and Analysis of Related Prognostic Factor. Studies in health technology and informatics. 316. 717–718. 1 indexed citations

Wang, Che-Chuan, et al.. (2024). Predictive Modeling of Long-Term Care Needs in Traumatic Brain Injury Patients Using Machine Learning. Diagnostics. 15(1). 20–20. 2 indexed citations

Shen, Yuting, et al.. (2024). Artificial intelligence prediction of In-Hospital mortality in patients with dementia: A multi-center study. International Journal of Medical Informatics. 191. 105590–105590. 4 indexed citations

Liao, Kuang‐Ming, et al.. (2023). Using an Artificial Intelligence Approach to Predict the Adverse Effects and Prognosis of Tuberculosis. Diagnostics. 13(6). 1075–1075. 11 indexed citations

Yu, Tzu‐Chieh, et al.. (2023). Machine Learning Algorithm Predicts Mortality Risk in Intensive Care Unit for Patients with Traumatic Brain Injury. Diagnostics. 13(18). 3016–3016. 8 indexed citations

Liu, Chung‐Feng, et al.. (2023). Machine Learning Approach for Prediction of the Test Results of Gonadotropin-Releasing Hormone Stimulation: Model Building and Implementation. Diagnostics. 13(9). 1550–1550. 6 indexed citations

Kao, Yuan, Chung‐Feng Liu, Chien‐Chin Hsu, et al.. (2023). External validation of geriatric influenza death score: A multicenter study. PLoS ONE. 18(3). e0283475–e0283475. 1 indexed citations

10.

Liu, Chung‐Feng, et al.. (2023). Development of real-time individualized risk prediction models for contrast associated acute kidney injury and 30-day dialysis after contrast enhanced computed tomography. European Journal of Radiology. 167. 111034–111034. 3 indexed citations

11.

Chen, Chia‐Jung, Yuting Shen, Chien‐Chin Hsu, et al.. (2023). Real‐time artificial intelligence predicts adverse outcomes in acute pancreatitis in the emergency department: Comparison with clinical decision rule. Academic Emergency Medicine. 31(2). 149–155. 11 indexed citations

12.

Kao, Yuan, Chien‐Chin Hsu, Chia‐Jung Chen, et al.. (2023). Using artificial intelligence to predict adverse outcomes in emergency department patients with hyperglycemic crises in real time. BMC Endocrine Disorders. 23(1). 234–234. 7 indexed citations

13.

Liu, Chung‐Feng, et al.. (2022). Implementation of a patient-centered mobile shared decision making platform and healthcare workers’ evaluation: a case in a medical center. Informatics for Health and Social Care. 48(1). 68–79. 3 indexed citations

14.

Liu, Chung‐Feng, Shian-Chin Ko, Kuo-Chen Cheng, et al.. (2022). An artificial intelligence system to predict the optimal timing for mechanical ventilation weaning for intensive care unit patients: A two-stage prediction approach. Frontiers in Medicine. 9. 935366–935366. 23 indexed citations

15.

Liu, Chung‐Feng, Hung‐Jung Lin, Chien‐Chin Hsu, et al.. (2022). Design and Implementation of a Comprehensive AI Dashboard for Real-Time Prediction of Adverse Prognosis of ED Patients. Healthcare. 10(8). 1498–1498. 12 indexed citations

16.

Chang, Wei‐Ting, Chung‐Feng Liu, Yin‐Hsun Feng, et al.. (2022). An artificial intelligence approach for predicting cardiotoxicity in breast cancer patients receiving anthracycline. Archives of Toxicology. 96(10). 2731–2737. 27 indexed citations

17.

Wang, Jhi‐Joung, et al.. (2022). Implementation of a machine learning application in preoperative risk assessment for hip repair surgery. BMC Anesthesiology. 22(1). 116–116. 22 indexed citations

18.

Hsu, Chien‐Chin, Chia‐Jung Chen, Hung‐Jung Lin, et al.. (2021). Predicting outcomes in older ED patients with influenza in real time using a big data-driven and machine learning approach to the hospital information system. BMC Geriatrics. 21(1). 280–280. 21 indexed citations

19.

Hsu, Chien‐Chin, Yuan Kao, Chia‐Jung Chen, et al.. (2020). Real-time AI prediction for major adverse cardiac events in emergency department patients with chest pain. Scandinavian Journal of Trauma Resuscitation and Emergency Medicine. 28(1). 93–93. 38 indexed citations

20.

Chang, I‐Chiu, et al.. (2007). A Study of Career Anchors and Job Characteristic Preferences of is Students. Journal of Computer Information Systems. 47(3). 24–33. 9 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.

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