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.
Association of Apolipoprotein E Genotypes With Lipid Levels and Coronary Risk
2007610 citationsAnders Ahlbom, Ulf dé Fairé et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Anders Ahlbom'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 Anders Ahlbom with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anders Ahlbom more than expected).
This network shows the impact of papers produced by Anders Ahlbom. 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 Anders Ahlbom. The network helps show where Anders Ahlbom may publish in the future.
Co-authorship network of co-authors of Anders Ahlbom
This figure shows the co-authorship network connecting the top 25 collaborators of Anders Ahlbom.
A scholar is included among the top collaborators of Anders Ahlbom 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 Anders Ahlbom. Anders Ahlbom is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Agardh, Emilie, Anders Ahlbom, Tomas Andersson, et al.. (2004). Explanations of socioeconomic differences in excess risk of type 2 diabetes in Swedish men and women : Diabetes Care. Diabetes Care. 27(3).15 indexed citations
7.
Fransson, Eleonor I., U de Faire, Anders Ahlbom, et al.. (2004). The risk of acute myocardial infarction: interactions of types of physical activity : Epidemiology. Epidemiology. 15(5).5 indexed citations
8.
Ahlbom, Anders, Maria Feychting, Anita Gustavsson, et al.. (2004). Occupational magnetic field exposure and myocardial infarction incidence : Epidemiology. Epidemiology. 15(4).1 indexed citations
9.
Agardh, Emilie, Anders Ahlbom, Tomas Andersson, et al.. (2003). Work stress and low sense of coherence is associated with type 2 diabetes in middle-aged Swedish women : Diabetes Care. Diabetes Care. 26(3).13 indexed citations
Wiman, B., Tomas Andersson, Johan Hallqvist, et al.. (2000). Plasma levels of tissue plasminogen activator/plasminogen activator inhibitor-1 complex and von Willebrand factor are significant risk markers for recurrent myocardial infarction in the Stockholm Heart Epidemiology Program (SHEEP) study : Arteriosclerosis, Thrombosis, and Vascular Biology. Arteriosclerosis Thrombosis and Vascular Biology. 20(8).12 indexed citations
12.
Hallqvist, Johan, Jette Möller, Anders Ahlbom, et al.. (2000). Does heavy physical exertion trigger myocardial infarction? A case-crossover analysis nested in a population-based case-referent study : American Journal of Epidemiology. American Journal of Epidemiology. 151(5).12 indexed citations
Repacholi, Michael H., M. Grandolfo, Anders Ahlbom, et al.. (1996). Health issues related to the use of hand-held radiotelephones and base transmitters. Health Physics. 70(4). 587–593.83 indexed citations
Feychting, Maria & Anders Ahlbom. (1992). [Cancer and magnetic fields in persons living close to high voltage power lines in Sweden].. PubMed. 89(50). 4371–4.4 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.