Maxine Mackintosh

1.2k total citations
10 papers, 314 citations indexed

About

Maxine Mackintosh is a scholar working on General Health Professions, Artificial Intelligence and Genetics. According to data from OpenAlex, Maxine Mackintosh has authored 10 papers receiving a total of 314 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in General Health Professions, 3 papers in Artificial Intelligence and 3 papers in Genetics. Recurrent topics in Maxine Mackintosh's work include Genomics and Rare Diseases (2 papers), Ethics in Clinical Research (2 papers) and Genetic Associations and Epidemiology (2 papers). Maxine Mackintosh is often cited by papers focused on Genomics and Rare Diseases (2 papers), Ethics in Clinical Research (2 papers) and Genetic Associations and Epidemiology (2 papers). Maxine Mackintosh collaborates with scholars based in United Kingdom, United States and Gambia. Maxine Mackintosh's co-authors include Kadija Ferryman, Marzyeh Ghassemi, Roxanne E. Jensen, Christine M. Colvis, T. Beck, Karlie R. Sharma, Luca Foschini, Kenneth Gersing, Kenneth D. Mandl and Noel Southall and has published in prestigious journals such as New England Journal of Medicine, The Lancet and Nature Communications.

In The Last Decade

Maxine Mackintosh

9 papers receiving 308 citations

Peers

Maxine Mackintosh

HI

AI

RNMI

GHP

PHEOH

Sebastian Fritsch Germany

Natalia Norori United Kingdom

Florence M. Aellen Switzerland

Avery Smith United States

Dana Moukheiber United States

Rachael V. Phillips United States

Claudia E. Haupt United States

Mira Moukheiber United States

Abdullah H. Alreedy Saudi Arabia

Janny Xue Chen Ke Canada

Sebastian Fritsch Germany

Maxine Mackintosh

152 ×1.2

HI

77 ×0.7

AI

64 ×1.4

RNMI

34 ×0.8

GHP

45 ×1.2

PHEOH

Citations per year, relative to Maxine Mackintosh Maxine Mackintosh (= 1×) peers Sebastian Fritsch

Countries citing papers authored by Maxine Mackintosh

Since Specialization

Citations

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

Fields of papers citing papers by Maxine Mackintosh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maxine Mackintosh

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

All Works

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10 of 10 papers shown

1.

Cho, Yoonsu, Fabian Falck, Michael Katell, et al.. (2025). Methodological opportunities in genomic data analysis to advance health equity. Nature Reviews Genetics. 26(9). 635–649. 1 indexed citations

2.

Thu, Nguyễn Thị Hoài, Yoonsu Cho, Alona Sosinsky, et al.. (2025). Equity in cancer genomics in the UK: a cross-sectional analysis of a national cancer cohort. The Lancet Oncology. 26(7). 971–980. 1 indexed citations

3.

Mitra, Robin, Sarah F. McGough, Tapabrata Chakraborti, et al.. (2023). Learning from data with structured missingness. Nature Machine Intelligence. 5(1). 13–23. 30 indexed citations

4.

Mackintosh, Maxine, et al.. (2023). Optimal strategies for learning multi-ancestry polygenic scores vary across traits. Nature Communications. 14(1). 4023–4023. 6 indexed citations

5.

Ferryman, Kadija, Maxine Mackintosh, & Marzyeh Ghassemi. (2023). Considering Biased Data as Informative Artifacts in AI-Assisted Health Care. New England Journal of Medicine. 389(9). 833–838. 47 indexed citations

6.

Knight, Hannah, Sarah R Deeny, Jorgen Engmann, et al.. (2021). Challenging racism in the use of health data. The Lancet Digital Health. 3(3). e144–e146. 30 indexed citations

7.

Cutillo, Christine M., Karlie R. Sharma, Luca Foschini, et al.. (2020). Machine intelligence in healthcare—perspectives on trustworthiness, explainability, usability, and transparency. npj Digital Medicine. 3(1). 47–47. 197 indexed citations

8.

Mackintosh, Maxine, Robert W Aldridge, Martin N. Rossor, et al.. (2019). Dementia recognition, diagnosis, and treatment in the UK, 1997–2017: a change-point analysis. The Lancet. 394. S70–S70.

9.

Mackintosh, Maxine. (2017). Data is the Future of Healthcare. ITNOW. 59(1). 40–41. 1 indexed citations

10.

Mackintosh, Maxine, et al.. (2016). Towards High Quality Health Care and Sustainable Financing – the Role of Health Care Programmes. Global Policy. 8(S2). 46–59. 1 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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