Maya Reddy

726 citations
35 papers · 487 · h-index 11

Impact in

Papers in

Maya Reddy

32 papers receiving 464 citations

Peers

Maya Reddy
Comparison fields: 5 of 26
  • Obstetrics and Gynecology 285
  • Psychiatry and Mental health 35
  • Pediatrics, Perinatology and Child Health 10
  • Cellular and Molecular Neuroscience 12
  • Pharmacology 9
Replace Annet M. Aukes with:
Annet M. Aukes Netherlands
Molly Mattsson Ireland
Shobha H Mehta United States
Ineke R. Postma Netherlands
Gülay Rathfısch Türkiye
Emily W. Rosenthal United States
Francesca De Luca Italy
Della A. Campbell United States
VE Murphy Australia
Angelina Paolozza Canada
Maya Reddy relative to Annet M. Aukes Netherlands Annet M. Aukes's profile →
Citations per field
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Annet M. Aukes · 1×
Citations per year

Countries citing papers authored by Maya Reddy

Since Specialization
Citations

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

Fields of papers citing papers by Maya Reddy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201193
2 202068
3 202057
4 201942
5 202034
6 201918
7 202218
8 202317
9 201716
10 201814
11 202012
12 202211
13 201910
14 20198
15 20228
16 20237
17 20156
18 20196
19 20206
20 20216

About Maya Reddy

Maya Reddy is a scholar working on Obstetrics and Gynecology, Pediatrics, Perinatology and Child Health, Epidemiology, Statistics, Probability and Uncertainty and Psychiatry and Mental health, having authored 35 papers that have together received 487 indexed citations. Recurring topics across this work include Pregnancy and preeclampsia studies (18 papers), Preterm Birth and Chorioamnionitis (2 papers), Schizophrenia research and treatment (1 paper), Telemedicine and Telehealth Implementation (1 paper), Fetal and Pediatric Neurological Disorders (1 paper), Congenital Heart Disease Studies (1 paper), Gestational Diabetes Research and Management (1 paper) and Meta-analysis and systematic reviews (1 paper). The work is most often cited by research in Obstetrics and Gynecology (285 citations), Psychiatry and Mental health (35 citations), Pediatrics, Perinatology and Child Health (10 citations), Cellular and Molecular Neuroscience (12 citations) and Pharmacology (9 citations). Maya Reddy has collaborated with scholars based in Australia, Brazil and Austria. Frequent co-authors include Ben W. Mol, Daniel L. Rolnik, Kirsten Rebecca Palmer, Fabrício da Silva Costa, Wentao Li, Euan Morrison Wallace, Didier Pinault, Terence John O'Brien, Paul Anderson and Michael R Salzberg. Their work appears in journals such as Australian and New Zealand Journal of Obstetrics and Gynaecology, Acta Obstetricia Et Gynecologica Scandinavica, BMC Pregnancy and Childbirth, Placenta and American Journal of Obstetrics and Gynecology.

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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