Nils D. Forkert

234 papers receiving 4.3k citations

Nils D. Forkert's Hit Papers

Machine learning for precision medicine 2020 · 279 citations
2790+2+4Years since publication50100150200250

Peers

Nils D. Forkert
Comparison fields: 5 of 168
  • Health Informatics 93
  • Neurology 574
  • Neurology 314
  • Epidemiology 1.0k
  • Rehabilitation 192
Replace Kei Yamada with:
Kei Yamada Japan
Birgit Ertl‐Wagner Germany
Toshinori Hirai Japan
Greg Zaharchuk United States
Chul‐Ho Sohn South Korea
Hannu J. Aronen Finland
Jean‐Pierre Pruvo France
Mary Rutherford United Kingdom
Beom Joon Kim South Korea
David M. Yousem United States
Nils D. Forkert relative to Kei Yamada Japan Kei Yamada's profile →
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Citations per year

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-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 242 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Machine learning for precision medicine
Hit paper breakdown →
2020279
2 2014171
3 2017168
4 2015112
5 2021108
6 2020108
7 2018106
8 2015105
9 201588
10 202084
11 202080
12 202064
13 201457
14 201256
15 202155
16 201547
17 201246
18 201646
19 201746
20 202145

About Nils D. Forkert

Nils D. Forkert is a scholar working on Epidemiology, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Neurology and Computer Vision and Pattern Recognition, having authored 242 papers that have together received 4.3k indexed citations. Recurring topics across this work include Acute Ischemic Stroke Management (59 papers), Cerebrovascular and Carotid Artery Diseases (36 papers), Advanced MRI Techniques and Applications (18 papers), Advanced Neuroimaging Techniques and Applications (18 papers), Dementia and Cognitive Impairment Research (17 papers), Medical Image Segmentation Techniques (15 papers), Functional Brain Connectivity Studies (15 papers) and Parkinson's Disease Mechanisms and Treatments (13 papers). The work is most often cited by research in Health Informatics (93 citations), Neurology (574 citations), Neurology (314 citations), Epidemiology (1.0k citations) and Rehabilitation (192 citations). Nils D. Forkert has collaborated with scholars based in Canada, Germany and United States. Frequent co-authors include Jens Fiehler, Sarah J. MacEachern, Pauline Mouchès, Götz Thomalla, Zahinoor Ismail, Matthias Wilms, Deepthi Rajashekar, Heinz Handels, Eric E. Smith and Bastian Cheng. Their work appears in journals such as Clinical Neuroradiology, American Journal of Neuroradiology, PLoS ONE, Frontiers in Neurology and Scientific Reports.

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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