Nadieh Khalili

446 total citations
8 papers, 140 citations indexed

About

Nadieh Khalili is a scholar working on Pediatrics, Perinatology and Child Health, Artificial Intelligence and Epidemiology. According to data from OpenAlex, Nadieh Khalili has authored 8 papers receiving a total of 140 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Pediatrics, Perinatology and Child Health, 4 papers in Artificial Intelligence and 2 papers in Epidemiology. Recurrent topics in Nadieh Khalili's work include Neonatal and fetal brain pathology (4 papers), Fetal and Pediatric Neurological Disorders (4 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Nadieh Khalili is often cited by papers focused on Neonatal and fetal brain pathology (4 papers), Fetal and Pediatric Neurological Disorders (4 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Nadieh Khalili collaborates with scholars based in Netherlands, Australia and France. Nadieh Khalili's co-authors include Nathalie H.P. Claessens, Roel de Heus, Elise Turk, Ivana Išgum, Manon J.N.L. Benders, Max A. Viergever, Nikolas Leßmann, Johannes M. P. J. Breur, Nienke Wagenaar and Pim Moeskops and has published in prestigious journals such as American Journal of Neuroradiology, Medical Image Analysis and Magnetic Resonance Imaging.

In The Last Decade

Nadieh Khalili

7 papers receiving 138 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Nadieh Khalili Netherlands	5	77	39	34	28	28	8	140
Kelly Payette United Kingdom	6	82 1.1×	45 1.2×	36 1.1×	21 0.8×	9 0.3×	27	121
M Aparicio Italy	4	41 0.5×	65 1.7×	10 0.3×	38 1.4×	6 0.2×	4	215
Jianwei Lin China	9	21 0.3×	78 2.0×	18 0.5×	38 1.4×	17 0.6×	33	203
Kevin Keraudren United Kingdom	7	199 2.6×	103 2.6×	72 2.1×	50 1.8×	20 0.7×	8	258
Oliver Gloger Germany	7	15 0.2×	62 1.6×	43 1.3×	83 3.0×	13 0.5×	11	161
Alan Glover United Kingdom	5	134 1.7×	119 3.1×	27 0.8×	19 0.7×	10 0.4×	6	213
A Freitas Portugal	2	6 0.1×	83 2.1×	34 1.0×	58 2.1×	6 0.2×	3	149
Shaozheng He China	6	19 0.2×	11 0.3×	9 0.3×	6 0.2×	20 0.7×	19	67
Carlo Biffi United Kingdom	5	5 0.1×	114 2.9×	30 0.9×	58 2.1×	9 0.3×	8	194
Pavan Annangi India	6	7 0.1×	86 2.2×	36 1.1×	31 1.1×	3 0.1×	12	125

Countries citing papers authored by Nadieh Khalili

Since Specialization

Citations

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

Fields of papers citing papers by Nadieh Khalili

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nadieh Khalili

This figure shows the co-authorship network connecting the top 25 collaborators of Nadieh Khalili. A scholar is included among the top collaborators of Nadieh Khalili 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 Nadieh Khalili. Nadieh Khalili is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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8 of 8 papers shown

1.

Litjens, Geert, et al.. (2025). Navigating the landscape of multimodal AI in medicine: A scoping review on technical challenges and clinical applications. Medical Image Analysis. 105. 103621–103621. 9 indexed citations

2.

Montezuma, Diana, Rouven Porz, Vincenzo L’Imperio, et al.. (2025). Unbiased Artificial Intelligence: Addressing Bias in Computational Pathology. PubMed. 3(4). 100302–100302.

3.

Khalili, Nadieh & Francesco Ciompi. (2024). Scaling data toward pan-cancer foundation models. Trends in cancer. 10(10). 871–872. 2 indexed citations

4.

Litjens, Geert, et al.. (2024). Navigating the landscape of multimodal AI in medicine: a scoping review on technical challenges and clinical applications. arXiv (Cornell University). 1 indexed citations

5.

Baak, Lisanne M., Nadieh Khalili, Henk A. Marquering, et al.. (2023). Brain segmentation in patients with perinatal arterial ischemic stroke. NeuroImage Clinical. 38. 103381–103381. 6 indexed citations

6.

Khalili, Nadieh, Elise Turk, Manon J.N.L. Benders, et al.. (2019). Automatic extraction of the intracranial volume in fetal and neonatal MR scans using convolutional neural networks. NeuroImage Clinical. 24. 102061–102061. 22 indexed citations

7.

Claessens, Nathalie H.P., Nadieh Khalili, Ivana Išgum, et al.. (2019). Brain and CSF Volumes in Fetuses and Neonates with Antenatal Diagnosis of Critical Congenital Heart Disease: A Longitudinal MRI Study. American Journal of Neuroradiology. 40(5). 885–891. 26 indexed citations

8.

Khalili, Nadieh, Nikolas Leßmann, Elise Turk, et al.. (2019). Automatic brain tissue segmentation in fetal MRI using convolutional neural networks. Magnetic Resonance Imaging. 64. 77–89. 74 indexed citations

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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