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Maxine Mackintosh
Maxine Mackintosh
Visiting Researcher, Alan Turing Institute
Verified email at turing.ac.uk
Title
Cited by
Cited by
Year
Machine intelligence in healthcare—perspectives on trustworthiness, explainability, usability, and transparency
CM Cutillo, KR Sharma, L Foschini, S Kundu, M Mackintosh, KD Mandl, ...
NPJ digital medicine 3 (1), 47, 2020
2652020
Considering biased data as informative artifacts in AI-assisted health care
K Ferryman, M Mackintosh, M Ghassemi
New England Journal of Medicine 389 (9), 833-838, 2023
652023
Tackling bias in AI health datasets through the STANDING Together initiative
S Ganapathi, J Palmer, JE Alderman, M Calvert, C Espinoza, J Gath, ...
Nature Medicine 28 (11), 2232-2233, 2022
642022
Challenging racism in the use of health data
HE Knight, SR Deeny, K Dreyer, J Engmann, M Mackintosh, S Raza, ...
The lancet digital health 3 (3), e144-e146, 2021
532021
Learning from data with structured missingness
R Mitra, SF McGough, T Chakraborti, C Holmes, R Copping, ...
Nature Machine Intelligence 5 (1), 13-23, 2023
452023
Machine intelligence in healthcare—perspectives on trustworthiness, explainability, usability, and transparency. npj Digital Medicine, 3 (1): 47, Mar 2020
CM Cutillo, KR Sharma, L Foschini, S Kundu, M Mackintosh, KD Mandl
ISSN, 2020
152020
Machine intelligence in healthcare—perspectives on trustworthiness, explainability, usability, and transparency, NPJ Digit Med. 3 (2020)
CM Cutillo, KR Sharma, L Foschini, S Kundu, M Mackintosh, KD Mandl, ...
11
Machine intelligence in healthcare—perspectives on trustworthiness, explainability, usability, and transparency. npj Digital Medicine 2020; 3 (1): 47
CM Cutillo, KR Sharma, L Foschini, S Kundu, M Mackintosh, KD Mandl, ...
DOI, 0
10
MI in Healthcare Workshop Working Group: Machine intelligence in healthcare-perspectives on trustworthiness, explainability, usability, and transparency
CM Cutillo, KR Sharma, L Foschini, S Kundu, M Mackintosh, KD Mandl
NPJ Digit Med 3, 47, 2020
92020
MI in Healthcare Workshop Working Group Beck Tyler 1 Collier Elaine 1 Colvis Christine 1 Gersing Kenneth 1 Gordon Valery 1 Jensen Roxanne 8 Shabestari Behrouz 9 Southall Noel 1 …
CM Cutillo, KR Sharma, L Foschini, S Kundu, M Mackintosh, KD Mandl
Machine intelligence in healthcare—perspectives on trustworthiness …, 2020
92020
The ethical challenges of diversifying genomic data: A qualitative evidence synthesis
F Hardcastle, K Lyle, R Horton, G Samuel, S Weller, L Ballard, ...
Cambridge Prisms: Precision Medicine 2, e1, 2024
62024
Optimal strategies for learning multi-ancestry polygenic scores vary across traits
B Lehmann, M Mackintosh, G McVean, C Holmes
Nature Communications 14 (1), 4023, 2023
62023
High trait variability in optimal polygenic prediction strategy within multiple-ancestry cohorts
BCL Lehmann, M Mackintosh, G McVean, CC Holmes
bioRxiv, 2021.01. 15.426781, 2021
52021
Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations
JE Alderman, J Palmer, E Laws, MD McCradden, J Ordish, M Ghassemi, ...
The Lancet Digital Health 7 (1), e64-e88, 2025
32025
Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review
E Laws, J Palmer, J Alderman, O Sharma, V Ngai, T Salisbury, G Hussain, ...
Clinical imaging, 110369, 2024
22024
Ethical, legal and social issues in diversifying genomic data: literature review and synthesis
F Hardcastle, L Ballard, S Weller, K Lyle, R Horton, G Samuel, ...
22022
Dementia recognition, diagnosis, and treatment in the UK, 1997–2017: a change-point analysis
M Mackintosh, RW Aldridge, M Rossor, A Gonzalez-Izquierdo, ...
The Lancet 394, S70, 2019
22019
DATA IS THE FUTURE OF HEALTHCARE.
M Mackintosh
ITNOW 59 (1), 2017
12017
Using Primary Care Electronic Health Records to Investigate Preclinical Dementia: Development of a Methodological Toolkit
M Mackintosh
UCL (University College London), 2024
2024
Disparities in cancer genomics by ancestry in the 100,000 Genomes Project
T Nguyen, S Tallman, Y Cho, A Sosinsky, J Ambrose, S Thorn, ...
medRxiv, 2024.11. 14.24317310, 2024
2024
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