Shih-Tsung Han

688 total citations
16 papers, 474 citations indexed

About

Shih-Tsung Han is a scholar working on Epidemiology, Family Practice and Physiology. According to data from OpenAlex, Shih-Tsung Han has authored 16 papers receiving a total of 474 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Epidemiology, 3 papers in Family Practice and 3 papers in Physiology. Recurrent topics in Shih-Tsung Han's work include Sepsis Diagnosis and Treatment (6 papers), Clinical Reasoning and Diagnostic Skills (3 papers) and COVID-19 Clinical Research Studies (2 papers). Shih-Tsung Han is often cited by papers focused on Sepsis Diagnosis and Treatment (6 papers), Clinical Reasoning and Diagnostic Skills (3 papers) and COVID-19 Clinical Research Studies (2 papers). Shih-Tsung Han collaborates with scholars based in Taiwan and United States. Shih-Tsung Han's co-authors include Kuan‐Fu Chen, Chin‐Chieh Wu, Deane F. Mosher, Chih-Huang Li, Chun‐Fu Yeh, Su‐Hsun Liu, Zhen-Ying Liu, Chung‐Hsien Chaou, William W. Busse and Mats W. Johansson and has published in prestigious journals such as American Journal of Respiratory and Critical Care Medicine, International Journal of Molecular Sciences and Medicine.

In The Last Decade

Shih-Tsung Han

16 papers receiving 460 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shih-Tsung Han Taiwan	10	213	127	82	78	66	16	474
Luis García de Guadiana‐Romualdo Spain	15	313 1.5×	117 0.9×	33 0.4×	143 1.8×	38 0.6×	49	724
Eberhard Spanuth Germany	12	283 1.3×	126 1.0×	27 0.3×	106 1.4×	34 0.5×	30	650
Stefania Battista Italy	10	326 1.5×	160 1.3×	48 0.6×	115 1.5×	19 0.3×	35	543
Katrin Ludewig Germany	10	137 0.6×	91 0.7×	47 0.6×	30 0.4×	28 0.4×	12	418
Liliana Tejidor United States	8	319 1.5×	112 0.9×	18 0.2×	136 1.7×	57 0.9×	11	491
Chin‐Chieh Wu Taiwan	11	321 1.5×	90 0.7×	19 0.2×	119 1.5×	40 0.6×	29	476
Matt Thomas United Kingdom	12	127 0.6×	69 0.5×	41 0.5×	25 0.3×	87 1.3×	36	488
Αιμιλία Πελεκάνου Greece	15	264 1.2×	102 0.8×	20 0.2×	48 0.6×	42 0.6×	26	582
John D’Angelo United States	12	271 1.3×	167 1.3×	34 0.4×	21 0.3×	98 1.5×	19	489
Hollis R. O’Neal United States	13	204 1.0×	80 0.6×	28 0.3×	28 0.4×	63 1.0×	35	560

Countries citing papers authored by Shih-Tsung Han

Since Specialization

Citations

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

Fields of papers citing papers by Shih-Tsung Han

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shih-Tsung Han. 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 Shih-Tsung Han. The network helps show where Shih-Tsung Han may publish in the future.

Co-authorship network of co-authors of Shih-Tsung Han

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

All Works

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16 of 16 papers shown

Chen, Kuan‐Fu, Chin‐Chieh Wu, Ismaeel Yunusa, et al.. (2023). Diagnostic accuracy of clinical signs and symptoms of COVID-19: A systematic review and meta-analysis to investigate the different estimates in a different stage of the pandemic outbreak. Journal of Global Health. 13. 6026–6026. 7 indexed citations

Tay, Joyce, Eric Chou, Chih‐Hung Wang, et al.. (2023). Development and External Validation of Clinical Features-based Machine Learning Models for Predicting COVID-19 in the Emergency Department. Western Journal of Emergency Medicine. 25(1). 67–78. 1 indexed citations

Han, Shih-Tsung, et al.. (2020). Current Evidence and Limitation of Biomarkers for Detecting Sepsis and Systemic Infection. Biomedicines. 8(11). 494–494. 51 indexed citations

Chen, Kuan‐Fu, et al.. (2019). Effectiveness of Treatments and Diagnostic Tools and Declining Mortality in Patients With Severe Sepsis: A 12-Year Population-Based Cohort Study. Journal of Intensive Care Medicine. 35(12). 1418–1425. 3 indexed citations

Wu, Chin‐Chieh, Shih-Tsung Han, Chung‐Hsien Chaou, et al.. (2017). Comparison of diagnostic accuracy in sepsis between presepsin, procalcitonin, and C-reactive protein: a systematic review and meta-analysis. Annals of Intensive Care. 7(1). 91–91. 137 indexed citations

Chen, Yu‐Hsien, et al.. (2017). The number of displaced rib fractures is more predictive for complications in chest trauma patients. Scandinavian Journal of Trauma Resuscitation and Emergency Medicine. 25(1). 19–19. 67 indexed citations

Han, Shih-Tsung, et al.. (2017). Transfusion of Red Blood Cells to Patients with Sepsis. International Journal of Molecular Sciences. 18(9). 1946–1946. 13 indexed citations

Han, Shih-Tsung, et al.. (2016). Systemic inflammatory response syndrome is more associated with bacteremia in elderly patients with suspected sepsis in emergency departments. Medicine. 95(49). e5634–e5634. 16 indexed citations

Chen, Kuan‐Fu, Su‐Hsun Liu, Chih-Huang Li, et al.. (2016). Development and validation of a parsimonious and pragmatic CHARM score to predict mortality in patients with suspected sepsis. The American Journal of Emergency Medicine. 35(4). 640–646. 20 indexed citations

10.

Han, Shih-Tsung & Deane F. Mosher. (2013). IL-5 Induces Suspended Eosinophils to Undergo Unique Global Reorganization Associated with Priming. American Journal of Respiratory Cell and Molecular Biology. 50(3). 654–664. 21 indexed citations

11.

Johansson, Mats W., et al.. (2012). Platelet Activation, P-Selectin, and Eosinophil β1-Integrin Activation in Asthma. American Journal of Respiratory and Critical Care Medicine. 185(5). 498–507. 81 indexed citations

12.

Johansson, Mats W., Shih-Tsung Han, Robert R. Montgomery, et al.. (2011). Platelet Activation, P-Selectin Mobilization, And Eosinophil Beta1 Integrin Activation Occur In Asthma And Are Associated With Clinical Phenotypes. A4335–A4335. 3 indexed citations

13.

Han, Shih-Tsung, Veena M. Bhopale, & Stephen R. Thom. (2007). Xanthine oxidoreductase and neurological sequelae of carbon monoxide poisoning. Toxicology Letters. 170(2). 111–115. 27 indexed citations

14.

Han, Shih-Tsung, et al.. (2003). Cardiac toxicity caused by Achyranthes aspera.. PubMed. 45(4). 212–3. 7 indexed citations

15.

McCammon, D., R. Almy, E. Apodaca, et al.. (1999). High-resolution calorimetry: limitations of doped semiconductor thermometers. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 436(1-2). 205–211. 6 indexed citations

16.

Han, Shih-Tsung, R. Almy, E. Apodaca, et al.. (1998). <title>Intrinsic 1/f noise in doped silicon thermistors for cryogenic calorimeters</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 3445. 640–644. 14 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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