Shiying Hao

1.6k citations
43 papers · 774 indexed · h-index 15
Topics
Chronic Disease Management Strategies (6 papers)Machine Learning in Healthcare (5 papers)Kawasaki Disease and Coronary Complications (5 papers)

In The Last Decade

Shiying Hao

41 papers receiving 759 citations

Peers

Shiying Hao
Comparison fields: 5 of 112
  • Epidemiology 194
  • Artificial Intelligence 167
  • Cardiology and Cardiovascular Medicine 137
  • Health Information Management 119
  • Pulmonary and Respiratory Medicine 104
Replace Lucinda Archer with:
Lucinda Archer United Kingdom
Eric Widen United States
Chunqing Zhu China
Frank Stearns United States
Shaun T Alfreds United States
Anne de Hond Netherlands
Sacha E. Bleeker Netherlands
Suzann Pershing United States
Chava L. Ramspek Netherlands
Ira Hofer United States
Shiying Hao relative to Lucinda Archer United Kingdom Lucinda Archer's profile →
Citations per field
00.5×9.8×
Lucinda Archer · 1×
Citations per year

Countries citing papers authored by Shiying Hao

Since Specialization
Citations

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

Fields of papers citing papers by Shiying Hao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shiying Hao

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 21
2 15
3
A Deep-Learning Based Prediction of Pancreatic Adenocarcinoma with Electronic Health Records from the State of Maine
4
4 8
5 64
6 58
7 35
8 38
9 22
10 171
11 48
12 3
13 16
14 7
15 23
16 19
17 4
18 7
19 11
20 70

About Shiying Hao

Shiying Hao is a scholar working on Emergency Medicine, Epidemiology and Nephrology, having authored 43 papers that have together received 774 indexed citations. Recurring topics across this work include Chronic Disease Management Strategies (6 papers), Machine Learning in Healthcare (5 papers) and Kawasaki Disease and Coronary Complications (5 papers). The work is most often cited by research in Health Informatics (61 citations), Health Information Management (119 citations) and Emergency Medicine (102 citations). Shiying Hao has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Xuefeng B. Ling, Karl G. Sylvester, Eric Widen, Frank Stearns, Bo Jin, Doff B. McElhinney, Shaun T Alfreds, Chunqing Zhu, Minjie Xia and Modi Liu. Their work appears in journals such as Circulation, Journal of Clinical Oncology and PLoS ONE.

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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