Anna See

36 papers receiving 701 citations

Anna See's Hit Papers

Prognosis and persistence of smell and taste dysfunction in patients with covid-19: meta-analysis with parametric cure modelling of recovery curves 2022 · 141 citations
1410+1+2Years since publication4080120

Peers

Anna See
Comparison fields: 5 of 70
  • Sensory Systems 141
  • Genetics 188
  • Endocrine and Autonomic Systems 42
  • Otorhinolaryngology 21
  • Physiology 124
Replace Anita Jeyakumar with:
Anita Jeyakumar United States
Victor Abdullah China
Yusuf Vayısoğlu Türkiye
Matthew G. Drake United States
Yavuz Selim Yıldırım Türkiye
Abdullah Ayçiçek Türkiye
Adın Selçuk Türkiye
Tae‐Bin Won South Korea
Song Tar Toh Singapore
Maurizio Iengo Italy
Anna See relative to Anita Jeyakumar United States Anita Jeyakumar's profile →
Citations per field
00.5×3.7×
Anita Jeyakumar · 1×
Citations per year

Countries citing papers authored by Anna See

Since Specialization
Citations

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

Fields of papers citing papers by Anna See

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1992208
2
Prognosis and persistence of smell and taste dysfunction in patients with covid-19: meta-analysis with parametric cure modelling of recovery curves
Hit paper breakdown →
2022141
3 202147
4 199828
5 202128
6 202228
7 202224
8 202321
9 202320
10 202217
11 202015
12 202214
13 202114
14 201713
15 202311
16 202210
17 202210
18 20219
19 20228
20 20168

About Anna See

Anna See is a scholar working on Physiology, Otorhinolaryngology, Pulmonary and Respiratory Medicine, Sensory Systems and Surgery, having authored 41 papers that have together received 714 indexed citations. Recurring topics across this work include Obstructive Sleep Apnea Research (13 papers), Head and Neck Cancer Studies (9 papers), Olfactory and Sensory Function Studies (5 papers), Tracheal and airway disorders (4 papers), Infection Control and Ventilation (2 papers), Thyroid Cancer Diagnosis and Treatment (2 papers), Thyroid and Parathyroid Surgery (2 papers) and Head and Neck Surgical Oncology (1 paper). The work is most often cited by research in Sensory Systems (141 citations), Genetics (188 citations), Endocrine and Autonomic Systems (42 citations), Otorhinolaryngology (21 citations) and Physiology (124 citations). Anna See has collaborated with scholars based in Singapore, Taiwan and United States. Frequent co-authors include Song Tar Toh, Benjamin Kye Jyn Tan, Nicole Kye Wen Tan, Yao Hao Teo, J C Soule, J Y Mary, E René, Dominic Wei Ting Yap, Antoine Cortot and Éric Lerebours. Their work appears in journals such as Otolaryngology, European Archives of Oto-Rhino-Laryngology, Head & Neck, Oral Oncology and American Journal of Otolaryngology.

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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