Ashley I. Naimi

4.4k citations
113 papers · 2.7k indexed · 2 hit papers · h-index 24
Topics
Advanced Causal Inference Techniques (38 papers)Pregnancy and preeclampsia studies (23 papers)Birth, Development, and Health (20 papers)
Journals
SHILAP Revista de lepidopterologíaAnnals of Internal MedicinePLoS ONE

In The Last Decade

Ashley I. Naimi

108 papers receiving 2.6k citations

Hit Papers

Big Data: A Revolution That Will Transform How We Live, W...201420262018202220142018100200300

Peers

Ashley I. Naimi
Comparison fields: 5 of 190
  • Statistics and Probability 495
  • Pediatrics, Perinatology and Child Health 408
  • Public Health, Environmental and Occupational Health 338
  • Health, Toxicology and Mutagenesis 324
  • General Health Professions 320
Replace Peng Ding with:
Peng Ding United States
Daniel Westreich United States
Véra Ehrenstein Denmark
Shaun R. Seaman United Kingdom
Oliver Kuß Germany
Gianluca Baio United Kingdom
Gillian Raab United Kingdom
Jeffrey S. Brown United States
Kazem Mohammad Iran
Charles Poole United Kingdom
Ashley I. Naimi relative to Peng Ding United States Peng Ding's profile →
Citations per field
00.5×4.4×
Peng Ding · 1×
Citations per year

Countries citing papers authored by Ashley I. Naimi

Since Specialization
Citations

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

Fields of papers citing papers by Ashley I. Naimi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ashley I. Naimi. 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 Ashley I. Naimi. The network helps show where Ashley I. Naimi may publish in the future.

Co-authorship network of co-authors of Ashley I. Naimi

This figure shows the co-authorship network connecting the top 25 collaborators of Ashley I. Naimi. A scholar is included among the top collaborators of Ashley I. Naimi 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 Ashley I. Naimi. Ashley I. Naimi 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 1
2 1
3 2
4 1
5 4
6 1
7 3
8 4
9 3
10 6
11 23
12 7
13 4
14 15
15 9
16 2
17 10
18 58
19 23
20 13

About Ashley I. Naimi

Ashley I. Naimi is a scholar working on Statistics and Probability, Obstetrics and Gynecology and Computational Mathematics, having authored 113 papers that have together received 2.7k indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (38 papers), Pregnancy and preeclampsia studies (23 papers) and Birth, Development, and Health (20 papers). The work is most often cited by research in Statistics and Probability (495 citations), Obstetrics and Gynecology (295 citations) and Health, Toxicology and Mutagenesis (324 citations). Ashley I. Naimi has collaborated with scholars based in United States, Canada and Ivory Coast. Frequent co-authors include Daniel Westreich, Stephen R. Cole, Laura B. Balzer, Brian W. Whitcomb, Edward H. Kennedy, Jay S. Kaufman, Nathalie Auger, Lisa M. Bodnar, David B. Richardson and Erica E. M. Moodie. Their work appears in journals such as SHILAP Revista de lepidopterología, Annals of Internal Medicine and PLoS ONE.

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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