Wei Hou

2.2k citations
40 papers · 529 · 1 hit paper · h-index 10

Impact in

    • COVID-19 Clinical Research Studies
    • SARS-CoV-2 and COVID-19 Research
  • Neurology top 10%
    • Long-Term Effects of COVID-19
    • Brain Tumor Detection and Classification

Papers in

Wei Hou

34 papers receiving 520 citations

Wei Hou's Hit Papers

VGG-TSwinformer: Transformer-based deep learning model for early Alzheimer’s disease prediction 2022 · 113 citations
1130+1+2Years since publication255075100

Peers

Wei Hou
Comparison fields: 5 of 84
  • Infectious Diseases 151
  • Neurology 58
  • Health Information Management 27
  • Neurology 68
  • Hepatology 30
Replace Enrico Longato with:
Enrico Longato Italy
Johad Khoury Israel
Xiaoping Yin China
Wenjuan Li China
James E. Brick United States
Louis Ho Shing Lau Hong Kong
JoonNyung Heo South Korea
Jun Zeng China
Wei Hou relative to Enrico Longato Italy Enrico Longato's profile →
Citations per field
00.5×8.3×
Enrico Longato · 1×
Citations per year

Countries citing papers authored by Wei Hou

Since Specialization
Citations

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

Fields of papers citing papers by Wei Hou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Wei Hou, 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 Wei Hou Line = papers co-authored together Wei Hou links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1
VGG-TSwinformer: Transformer-based deep learning model for early Alzheimer’s disease prediction
Hit paper breakdown →
2022113
2 202092
3 202079
4 202071
5 201020
6 200619
7 201117
8 201117
9 202112
10 201010
11 20229
12 20239
13 20228
14 20207
15 20207
16 20107
17 20245
18 20213
19 20143
20 20242

About Wei Hou

Wei Hou is a scholar working on Infectious Diseases, Neurology, Surgery, Pharmacology and Pathology and Forensic Medicine, having authored 40 papers that have together received 529 indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (7 papers), Long-Term Effects of COVID-19 (4 papers), COVID-19 and healthcare impacts (3 papers), Spine and Intervertebral Disc Pathology (3 papers), Pregnancy-related medical research (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Dental Health and Care Utilization (2 papers) and Musculoskeletal pain and rehabilitation (2 papers). The work is most often cited by research in Infectious Diseases (151 citations), Neurology (58 citations), Health Information Management (27 citations), Neurology (68 citations) and Hepatology (30 citations). Wei Hou has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Zhentao Hu, Zheng Wang, Yong Jin, Zhongjie Hu, Lianchun Liang, Bin Xu, Ronghua Jin, Wei Zhang, Mitchell L. Schubert and Lili Zhang. Their work appears in journals such as Spine, Frontiers in Pediatrics, Chemico-Biological Interactions, PLoS ONE and Frontiers in Microbiology.

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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