Sol Kaufman

897 citations
23 papers · 629 indexed · h-index 14
Topics
Advanced Causal Inference Techniques (8 papers)Statistical Methods and Inference (5 papers)Head and Neck Cancer Studies (5 papers)
Partner nations
United StatesCanada

In The Last Decade

Sol Kaufman

23 papers receiving 576 citations

Peers

Sol Kaufman
Comparison fields: 5 of 110
  • Statistics and Probability 164
  • Surgery 130
  • Physiology 126
  • Health 81
  • Economics and Econometrics 75
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Chonghua Wan China
Jessica Roydhouse Australia
Isabel de Salis United Kingdom
Veronica Sciannameo Italy
Yemi Oluboyede United Kingdom
Anthony Roman United States
Anne-Lise Septans France
Costanza Pizzi Italy
Mary Shaw United States
A. Penna Italy
Sol Kaufman relative to Chonghua Wan China Chonghua Wan's profile →
Citations per field
00.5×10×12.6×
Chonghua Wan · 1×
Citations per year

Countries citing papers authored by Sol Kaufman

Since Specialization
Citations

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

Fields of papers citing papers by Sol Kaufman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sol Kaufman

This figure shows the co-authorship network connecting the top 25 collaborators of Sol Kaufman. A scholar is included among the top collaborators of Sol Kaufman 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 Sol Kaufman. Sol Kaufman 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 29
2 41
3 36
4 191
5 4
6 45
7 2
8 33
9 15
10 6
11 17
12 17
13 3
14 4
15
[Familial myeloproliferative syndromes. Study of 6 families and review of literature].
2
16 20
17 1
18
OPTIMUM DEMODULATION OF PM AND FM SIGNALS
1
19 5
20 22

About Sol Kaufman

Sol Kaufman is a scholar working on Otorhinolaryngology, Statistics and Probability and Geriatrics and Gerontology, having authored 23 papers that have together received 629 indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (8 papers), Statistical Methods and Inference (5 papers) and Head and Neck Cancer Studies (5 papers). The work is most often cited by research in Statistics and Probability (164 citations), Health (81 citations) and Otorhinolaryngology (35 citations). Sol Kaufman has collaborated with scholars based in United States and Canada. Frequent co-authors include Jay S. Kaufman, Richard F. MacLehose, John M. Loré, Charles Poole, Charles Poole, Vahram Y. Bakamjian, Peter Reese, Kumao Sako, Mohamed S. Razack and Kenneth W. Terhune. Their work appears in journals such as Journal of Applied Physics, Social Science & Medicine and International Journal of Epidemiology.

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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