Daisy Saw

1.4k citations
40 papers · 1.2k · h-index 19

Impact in

    • Head and Neck Cancer Studies
  • Oncology top 10%
    • Viral-associated cancers and disorders
    • Vascular Tumors and Angiosarcomas

Papers in

Daisy Saw

40 papers receiving 1k citations

Peers

Daisy Saw
Comparison fields: 5 of 69
  • Otorhinolaryngology 174
  • Oncology 239
  • Endocrinology, Diabetes and Metabolism 116
  • Surgery 237
  • Pulmonary and Respiratory Medicine 147
Replace Kenneth A. Newkirk with:
Kenneth A. Newkirk United States
Devendra D. Patel India
Keiji Kodama Japan
Francisco José Martínez-Tello Spain
Tatsuru Ikeda Japan
G. Fischer Germany
Masaaki Nakahara Japan
Werner B�cker Germany
Satoshi Iwasa Japan
Paul C Smyth Ireland
Daisy Saw relative to Kenneth A. Newkirk United States Kenneth A. Newkirk's profile →
Citations per field
00.5×1.5×2.1×
Kenneth A. Newkirk · 1×
Citations per year

Countries citing papers authored by Daisy Saw

Since Specialization
Citations

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

Fields of papers citing papers by Daisy Saw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daisy Saw, 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 Daisy Saw Line = papers co-authored together Daisy Saw 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 1980206
2 1986102
3 1986101
4 198773
5
Carcinoma of the nasal and paranasal regions in rats fed Cantonese salted marine fish.
197866
6 200958
7 198157
8 199346
9 197842
10 198642
11 198638
12 199633
13 198731
14 198526
15 200124
16 197822
17 198622
18 198622
19 199519
20 198018

About Daisy Saw

Daisy Saw is a scholar working on Pulmonary and Respiratory Medicine, Surgery, Otorhinolaryngology, Rheumatology and Pathology and Forensic Medicine, having authored 40 papers that have together received 1.2k indexed citations. Recurring topics across this work include Sarcoma Diagnosis and Treatment (6 papers), Salivary Gland Tumors Diagnosis and Treatment (3 papers), Head and Neck Cancer Studies (3 papers), Bone Tumor Diagnosis and Treatments (2 papers), Clinical Laboratory Practices and Quality Control (2 papers), Genetic factors in colorectal cancer (2 papers), Viral-associated cancers and disorders (2 papers) and Adrenal and Paraganglionic Tumors (2 papers). The work is most often cited by research in Otorhinolaryngology (174 citations), Oncology (239 citations), Endocrinology, Diabetes and Metabolism (116 citations), Surgery (237 citations) and Pulmonary and Respiratory Medicine (147 citations). Daisy Saw has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include JOHN H. C. HO, W.H. Lau, John K. C. Chan, D. P. Huang, Man-Tien Lui, Y.F. Poon, ChiSing Ng, John K. C. Chan, Linda C. Koo and Tiaw Bee Teoh. Their work appears in journals such as Human Pathology, International Journal of Cancer, Pathology, The American Journal of Surgical Pathology and The Lancet.

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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