Heather Ames

1.5k total citations · 2 hit papers
39 papers, 821 citations indexed

About

Heather Ames is a scholar working on Health, Electrical and Electronic Engineering and Cognitive Neuroscience. According to data from OpenAlex, Heather Ames has authored 39 papers receiving a total of 821 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Health, 8 papers in Electrical and Electronic Engineering and 7 papers in Cognitive Neuroscience. Recurrent topics in Heather Ames's work include Vaccine Coverage and Hesitancy (11 papers), Advanced Memory and Neural Computing (8 papers) and Neural dynamics and brain function (7 papers). Heather Ames is often cited by papers focused on Vaccine Coverage and Hesitancy (11 papers), Advanced Memory and Neural Computing (8 papers) and Neural dynamics and brain function (7 papers). Heather Ames collaborates with scholars based in Norway, Australia and South Africa. Heather Ames's co-authors include Claire Glenton, Simon Lewin, Xavier Bosch‐Capblanch, Angela Oyo‐Ita, Jessica Kaufman, Gabriel Rada, Afiong Oku, Yuri Cartier, Sophie Hill and Artur Manuel Muloliwa and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Journal of the Acoustical Society of America.

In The Last Decade

Heather Ames

36 papers receiving 793 citations

Hit Papers

Purposive sampling in a qualitative evidence synthesis: a... 2017 2026 2020 2023 2019 2017 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Heather Ames Norway 14 233 149 118 100 91 39 821
Tom Koch Canada 16 49 0.2× 189 1.3× 108 0.9× 137 1.4× 191 2.1× 97 1.0k
Minsoo Jung South Korea 18 328 1.4× 458 3.1× 187 1.6× 341 3.4× 114 1.3× 133 1.3k
Ran Hu China 20 188 0.8× 130 0.9× 125 1.1× 332 3.3× 33 0.4× 107 1.5k
Jill A. Fisher United States 24 75 0.3× 396 2.7× 89 0.8× 292 2.9× 658 7.2× 85 1.8k
Xue Yang China 22 98 0.4× 179 1.2× 97 0.8× 698 7.0× 70 0.8× 115 1.6k
Mengdie Zhuang United Kingdom 6 57 0.2× 164 1.1× 120 1.0× 149 1.5× 97 1.1× 13 759
Kar‐Hai Chu United States 20 359 1.5× 235 1.6× 174 1.5× 496 5.0× 198 2.2× 66 1.6k
Lorie Donelle Canada 20 241 1.0× 482 3.2× 108 0.9× 327 3.3× 222 2.4× 95 1.3k
Andrea G. Parker United States 22 73 0.3× 344 2.3× 30 0.3× 347 3.5× 89 1.0× 66 1.4k
Jane Williams Australia 15 91 0.4× 140 0.9× 42 0.4× 106 1.1× 102 1.1× 67 617

Countries citing papers authored by Heather Ames

Since Specialization
Citations

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

Fields of papers citing papers by Heather Ames

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Heather Ames

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

All Works

20 of 20 papers shown
2.
Ames, Heather, Emma F. France, Sara Cooper, et al.. (2024). Assessing qualitative data richness and thickness: Development of an evidence‐based tool for use in qualitative evidence synthesis. SHILAP Revista de lepidopterología. 2(7). e12059–e12059. 4 indexed citations
3.
Muller, Ashley Elizabeth, Rigmor C. Berg, José F. Meneses-Echávez, et al.. (2023). The effect of machine learning tools for evidence synthesis on resource use and time-to-completion: protocol for a retrospective pilot study. Systematic Reviews. 12(1). 7–7. 7 indexed citations
4.
Glenton, Claire, Simon Lewin, Soo Downe, et al.. (2022). Cochrane Effective Practice and Organisation of Care (EPOC) Qualitative Evidence Syntheses, Differences From Reviews of Intervention Effectiveness and Implications for Guidance. International Journal of Qualitative Methods. 21. 17 indexed citations
5.
Jardim, Patricia Sofia Jacobsen, et al.. (2022). Automating risk of bias assessment in systematic reviews: a real-time mixed methods comparison of human researchers to a machine learning system. BMC Medical Research Methodology. 22(1). 167–167. 33 indexed citations
6.
Ames, Heather, et al.. (2021). Hvordan forstå og håndtere barn som avviser en forelder: En systematisk kartleggingsoversikt. Duo Research Archive (University of Oslo). 1 indexed citations
7.
Berg, Rigmor C., et al.. (2021). Konsekvenser av covid-19 på barn og unges liv og helse: en hurtigoversikt. Duo Research Archive (University of Oslo). 5 indexed citations
9.
Ames, Heather, et al.. (2019). Sammenhenger mellom foreldrepraksiser og barns trivsel: en systematisk kartleggingsoversikt. Duo Research Archive (University of Oslo).
10.
Ames, Heather, et al.. (2018). Community and Drug Distributor Perceptions and Experiences of Mass Drug Administration for the Elimination of Lymphatic Filariasis. Advances in Parasitology. 103. 117–149. 9 indexed citations
11.
Muloliwa, Artur Manuel, Julie Cliff, Afiong Oku, et al.. (2017). Using the COMMVAC taxonomy to map vaccination communication interventions in Mozambique. Global Health Action. 10(1). 1321313–1321313. 3 indexed citations
12.
Kaufman, Jessica, Heather Ames, Xavier Bosch‐Capblanch, et al.. (2017). The comprehensive ‘Communicate to Vaccinate’ taxonomy of communication interventions for childhood vaccination in routine and campaign contexts. BMC Public Health. 17(1). 423–423. 37 indexed citations
13.
Oku, Afiong, Angela Oyo‐Ita, Claire Glenton, et al.. (2017). Perceptions and experiences of childhood vaccination communication strategies among caregivers and health workers in Nigeria: A qualitative study. PLoS ONE. 12(11). e0186733–e0186733. 35 indexed citations
14.
Ames, Heather, Claire Glenton, Atle Fretheim, et al.. (2017). Stakeholder perceptions of communication about vaccination in two regions of Cameroon: A qualitative case study. PLoS ONE. 12(8). e0183721–e0183721. 19 indexed citations
15.
Kaufman, Jessica, Rebecca Ryan, Claire Glenton, et al.. (2017). Childhood vaccination communication outcomes unpacked and organized in a taxonomy to facilitate core outcome establishment. Journal of Clinical Epidemiology. 84. 173–184. 12 indexed citations
16.
Oku, Afiong, Angela Oyo‐Ita, Claire Glenton, et al.. (2017). Factors affecting the implementation of childhood vaccination communication strategies in Nigeria: a qualitative study. BMC Public Health. 17(1). 200–200. 82 indexed citations breakdown →
17.
Yoshizawa, Akihiko, Kevin M. Chan, Heather Ames, et al.. (2013). Quality Assurance. Laboratory Investigation. 93. 471–489. 1 indexed citations
18.
Ames, Heather, Ennio Mingolla, Ayesha Sohail, et al.. (2012). The Animat: New Frontiers in Whole Brain Modeling. IEEE Pulse. 3(1). 47–50. 9 indexed citations
19.
20.
Gorchetchnikov, Anatoli, Massimiliano Versace, Heather Ames, et al.. (2011). Review and unification of learning framework in Cog Ex Machina platform for memristive neuromorphic hardware. 2601–2608. 5 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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