Hsin-Chi Wu

474 citations
18 papers · 328 · h-index 9

Impact in

Papers in

Hsin-Chi Wu

17 papers receiving 323 citations

Peers

Hsin-Chi Wu
Comparison fields: 5 of 51
  • Cognitive Neuroscience 179
  • Developmental and Educational Psychology 94
  • Experimental and Cognitive Psychology 76
  • Molecular Medicine 17
  • Reproductive Medicine 22
Replace Karissa Searle with:
Karissa Searle Australia
Werner Sommer Germany
M. Tremblay Canada
Jonathan A. Berken United States
Aquiles Luna‐Rodriguez Germany
Karina Carlesso Pagliarin Brazil
Silvia Bonacina United States
Veronica P. Y. Kwok China
Elizabeth A. Wiemers United States
Cristina Ferraz Borges Murphy Brazil
Hsin-Chi Wu relative to Karissa Searle Australia Karissa Searle's profile →
Citations per field
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Karissa Searle · 1×
Citations per year

Countries citing papers authored by Hsin-Chi Wu

Since Specialization
Citations

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

Fields of papers citing papers by Hsin-Chi Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hsin-Chi Wu. 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 Hsin-Chi Wu. The network helps show where Hsin-Chi Wu may publish in the future.

Co-authors

The 24 scholars most cited alongside Hsin-Chi Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Hsin-Chi Wu Line = papers co-authored together Hsin-Chi Wu links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 201278
2 202157
3 201346
4 201543
5 201522
6
Diagnostic accuracy of the Motor Subtest of Comprehensive Developmental Inventory for Infants and Toddlers and the Peabody Developmental Motor Scales-Second Edition.
200516
7 201914
8 202013
9 201711
10 20137
11 20236
12 20215
13 20224
14 20233
15 20231
16 20221
17 20151
18 20250

About Hsin-Chi Wu

Hsin-Chi Wu is a scholar working on Cognitive Neuroscience, Developmental and Educational Psychology, Pediatrics, Perinatology and Child Health, Clinical Psychology and Experimental and Cognitive Psychology, having authored 18 papers that have together received 328 indexed citations. Recurring topics across this work include Family and Disability Support Research (4 papers), Neuroscience and Music Perception (4 papers), Autism Spectrum Disorder Research (3 papers), Phonetics and Phonology Research (3 papers), Language Development and Disorders (3 papers), Infant Development and Preterm Care (3 papers), Hearing Loss and Rehabilitation (3 papers) and Reading and Literacy Development (2 papers). The work is most often cited by research in Cognitive Neuroscience (179 citations), Developmental and Educational Psychology (94 citations), Experimental and Cognitive Psychology (76 citations), Molecular Medicine (17 citations) and Reproductive Medicine (22 citations). Hsin-Chi Wu has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Chia‐Ying Lee, Ming‐Tao Yang, Lulu Zhao, Meng‐Yu Wu, Chun‐Yu Chang, Wan-Hsuan Lin, Yi-Shiung Horng, Chih‐Hao Chen, Jong‐Ling Fuh and Grace Yao. Their work appears in journals such as Autism, Neuropsychologia, Nutrients, Developmental Neuropsychology and Learning and Motivation.

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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