Nils D. Forkert

7.3k total citations · 1 hit paper
242 papers, 4.2k citations indexed

About

Nils D. Forkert is a scholar working on Radiology, Nuclear Medicine and Imaging, Epidemiology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Nils D. Forkert has authored 242 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 96 papers in Radiology, Nuclear Medicine and Imaging, 74 papers in Epidemiology and 70 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Nils D. Forkert's work include Acute Ischemic Stroke Management (69 papers), Cerebrovascular and Carotid Artery Diseases (68 papers) and Advanced MRI Techniques and Applications (42 papers). Nils D. Forkert is often cited by papers focused on Acute Ischemic Stroke Management (69 papers), Cerebrovascular and Carotid Artery Diseases (68 papers) and Advanced MRI Techniques and Applications (42 papers). Nils D. Forkert collaborates with scholars based in Canada, Germany and United States. Nils D. Forkert's co-authors include Jens Fiehler, Sarah J. MacEachern, Götz Thomalla, Pauline Mouchès, Zahinoor Ismail, Matthias Wilms, Heinz Handels, Deepthi Rajashekar, Eric E. Smith and Bastian Cheng and has published in prestigious journals such as JAMA, ACS Nano and PLoS ONE.

In The Last Decade

Nils D. Forkert

235 papers receiving 4.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Machine learning for precision medicine

2020 271 citations Nils D. Forkert et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Nils D. Forkert Canada	33	1.2k	917	858	816	594	242	4.2k
Richard Beare Australia	39	863 0.7×	1.2k 1.3×	596 0.7×	584 0.7×	230 0.4×	240	5.1k
Arnd Dörfler Germany	40	1.3k 1.1×	1.6k 1.8×	946 1.1×	1.5k 1.8×	489 0.8×	210	5.4k
Karl Schaller Switzerland	43	830 0.7×	507 0.6×	677 0.8×	1.5k 1.8×	678 1.1×	228	6.0k
Eung Yeop Kim South Korea	37	865 0.7×	1.6k 1.8×	671 0.8×	1.0k 1.2×	473 0.8×	155	4.4k
Qi Yang China	33	845 0.7×	1.8k 2.0×	1.2k 1.4×	1.0k 1.3×	384 0.6×	277	4.2k
Koen L. Vincken Netherlands	41	538 0.5×	1.1k 1.2×	1.1k 1.3×	452 0.6×	438 0.7×	149	4.9k
Birgit Ertl‐Wagner Germany	48	1.3k 1.1×	1.5k 1.7×	856 1.0×	1.7k 2.1×	498 0.8×	276	7.5k
Arturo Brunetti Italy	46	676 0.6×	2.3k 2.5×	950 1.1×	1.4k 1.8×	550 0.9×	305	7.9k
Hugo J. Kuijf Netherlands	32	594 0.5×	1.2k 1.3×	722 0.8×	844 1.0×	172 0.3×	125	3.7k
Christopher G. Filippi United States	34	611 0.5×	1.6k 1.8×	355 0.4×	989 1.2×	307 0.5×	128	4.3k

Countries citing papers authored by Nils D. Forkert

Since Specialization

Citations

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

Fields of papers citing papers by Nils D. Forkert

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nils D. Forkert. 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 Nils D. Forkert. The network helps show where Nils D. Forkert may publish in the future.

Co-authorship network of co-authors of Nils D. Forkert

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

All Works

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20 of 20 papers shown

Vercio, Lucas Lo, Rebecca M. Green, Marta Vidal‐García, et al.. (2025). Quantifying the relationship between cell proliferation and morphology during development of the face. Development. 152(7).

Nielsen, Christopher D., Matthias Wilms, & Nils D. Forkert. (2025). A Novel Foundation Model-Based Framework for Multimodal Retinal Age Prediction. IEEE Journal of Translational Engineering in Health and Medicine. 13. 299–309. 1 indexed citations

Rajashekar, Deepthi, et al.. (2024). Spatial normalization for voxel-based lesion symptom mapping: impact of registration approaches. Frontiers in Neuroscience. 18. 1296357–1296357. 1 indexed citations

Cole, Lauran, Nils D. Forkert, Mary Dunbar, et al.. (2024). Risk Factors for Perinatal Arterial Ischemic Stroke. Neurology. 102(11). e209393–e209393. 2 indexed citations

Stelfox, Henry T., et al.. (2024). Using Domain Adaptation and Inductive Transfer Learning to Improve Patient Outcome Prediction in the Intensive Care Unit: Retrospective Observational Study. Journal of Medical Internet Research. 26. e52730–e52730. 2 indexed citations

Camicioli, Richard, et al.. (2024). Identifying Biases in a Multicenter MRI Database for Parkinson's Disease Classification: Is the Disease Classifier a Secret Site Classifier?. IEEE Journal of Biomedical and Health Informatics. 28(4). 2047–2054. 10 indexed citations

Forkert, Nils D., et al.. (2023). Self-supervised-RCNN for medical image segmentation with limited data annotation. Computerized Medical Imaging and Graphics. 109. 102297–102297. 14 indexed citations

Wilms, Matthias, et al.. (2023). The causal link between cardiometabolic risk factors and gray matter atrophy: An exploratory study. Heliyon. 9(11). e21567–e21567. 1 indexed citations

Renson, Thomas, Nils D. Forkert, Päivi Miettunen, et al.. (2023). Distinct phenotypes of multisystem inflammatory syndrome in children: a cohort study. Pediatric Rheumatology. 21(1). 33–33. 3 indexed citations

10.

Bannister, Jordan J., Matthias Wilms, J. David Aponte, et al.. (2022). A Deep Invertible 3-D Facial Shape Model for Interpretable Genetic Syndrome Diagnosis. IEEE Journal of Biomedical and Health Informatics. 26(7). 3229–3239. 11 indexed citations

11.

Wilms, Matthias, et al.. (2021). Treatment Efficacy Analysis in Acute Ischemic Stroke Patients Using In Silico Modeling Based on Machine Learning: A Proof-of-Principle. Biomedicines. 9(10). 1357–1357. 5 indexed citations

12.

Rajashekar, Deepthi, Matthias Wilms, M. Ethan MacDonald, et al.. (2021). Lesion-symptom mapping with NIHSS sub-scores in ischemic stroke patients. Stroke and Vascular Neurology. 7(2). 124–131. 21 indexed citations

13.

Subbanna, Nagesh K., Matthias Wilms, Anup Tuladhar, & Nils D. Forkert. (2021). An Analysis of the Vulnerability of Two Common Deep Learning-Based Medical Image Segmentation Techniques to Model Inversion Attacks. Sensors. 21(11). 3874–3874. 15 indexed citations

14.

Bannister, Jordan J., J. David Aponte, David C. Katz, et al.. (2020). Fully Automatic Landmarking of Syndromic 3D Facial Surface Scans Using 2D Images. Sensors. 20(11). 3171–3171. 19 indexed citations

15.

Rajashekar, Deepthi, Matthias Wilms, M. Ethan MacDonald, et al.. (2020). High-resolution T2-FLAIR and non-contrast CT brain atlas of the elderly. Scientific Data. 7(1). 56–56. 27 indexed citations

16.

Tuladhar, Anup, et al.. (2020). Automatic Segmentation of Stroke Lesions in Non-Contrast Computed Tomography Datasets With Convolutional Neural Networks. IEEE Access. 8. 94871–94879. 25 indexed citations

17.

Rajashekar, Deepthi, Pauline Mouchès, Jens Fiehler, et al.. (2020). Structural integrity of white matter tracts as a predictor of acute ischemic stroke outcome. International Journal of Stroke. 15(9). 965–972. 9 indexed citations

18.

Guo, Jen, Rani Gupta Sah, Bijoy K. Menon, et al.. (2020). Dynamic CTA-Derived Perfusion Maps Predict Final Infarct Volume: The Simple Perfusion Reconstruction Algorithm. American Journal of Neuroradiology. 41(11). 2034–2040. 9 indexed citations

19.

Sah, Rani Gupta, Deepthi Rajashekar, Pauline Mouchès, et al.. (2019). Temporal evolution and spatial distribution of quantitative T2 MRI following acute ischemia reperfusion injury. International Journal of Stroke. 15(5). 495–506. 5 indexed citations

20.

Figueiró-Filho, Ernesto Antônio, B. Anne Croy, James N. Reynolds, et al.. (2017). Diffusion Tensor Imaging of White Matter in Children Born from Preeclamptic Gestations. American Journal of Neuroradiology. 38(4). 801–806. 29 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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