Simon Nusinovici

2.6k citations
66 papers · 1.4k · 1 hit paper · h-index 19

Impact in

Papers in

Simon Nusinovici

63 papers receiving 1.4k citations

Simon Nusinovici's Hit Papers

Logistic regression was as good as machine learning for predicting major chronic diseases 2020 · 339 citations
3390+2+4Years since publication100200300

Peers

Simon Nusinovici
Comparison fields: 5 of 162
  • Health Informatics 54
  • Ophthalmology 355
  • Health Information Management 179
  • Radiology, Nuclear Medicine and Imaging 443
  • Parasitology 93
Replace Bo Zhang with:
Bo Zhang United States
Qi Gao China
Shefali Parikh India
Annie Mathai India
G. Chandra Sekhar India
Rajul Parikh India
Marco Carone United States
Ravi Thomas India
André Karch Germany
Hui Chen China
Simon Nusinovici relative to Bo Zhang United States Bo Zhang's profile →
Citations per field
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Citations per year

Countries citing papers authored by Simon Nusinovici

Since Specialization
Citations

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

Fields of papers citing papers by Simon Nusinovici

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 66 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Logistic regression was as good as machine learning for predicting major chronic diseases
Hit paper breakdown →
2020339
2 2020152
3 202086
4 202058
5 201556
6 202251
7 201936
8 202032
9 201329
10 201728
11 202125
12 202125
13 201024
14 202324
15 202224
16 201923
17 201523
18 201221
19 202119
20 202417

About Simon Nusinovici

Simon Nusinovici is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology, Ecology, Evolution, Behavior and Systematics, Pediatrics, Perinatology and Child Health and Agronomy and Crop Science, having authored 66 papers that have together received 1.4k indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (28 papers), Retinal Diseases and Treatments (20 papers), Glaucoma and retinal disorders (12 papers), Vector-Borne Animal Diseases (11 papers), Animal Disease Management and Epidemiology (9 papers), Infant Development and Preterm Care (7 papers), Artificial Intelligence in Healthcare (7 papers) and Retinal and Optic Conditions (7 papers). The work is most often cited by research in Health Informatics (54 citations), Ophthalmology (355 citations), Health Information Management (179 citations), Radiology, Nuclear Medicine and Imaging (443 citations) and Parasitology (93 citations). Simon Nusinovici has collaborated with scholars based in Singapore, France and United Kingdom. Frequent co-authors include Charumathi Sabanayagam, Ching‐Yu Cheng, Yih Chung Tham, Tien Yin Wong, Daniel Shu Wei Ting, Jialiang Li, François Beaudeau, Alain Joly, Stefan Widgrén and Ann Lindberg. Their work appears in journals such as PLoS ONE, British Journal of Ophthalmology, Scientific Reports, International Journal of Epidemiology and Preventive Veterinary Medicine.

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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