Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2020 Dec 9;27(12):2011-2015.
doi: 10.1093/jamia/ocaa088.

MINIMAR (MINimum Information for Medical AI Reporting): Developing reporting standards for artificial intelligence in health care

Tina Hernandez-Boussard  1   2   3 , Selen Bozkurt  1 , John P A Ioannidis  1   4   5 , Nigam H Shah  1   2
Affiliations

MINIMAR (MINimum Information for Medical AI Reporting): Developing reporting standards for artificial intelligence in health care

Tina Hernandez-Boussard et al. J Am Med Inform Assoc. .

Abstract

The rise of digital data and computing power have contributed to significant advancements in artificial intelligence (AI), leading to the use of classification and prediction models in health care to enhance clinical decision-making for diagnosis, treatment and prognosis. However, such advances are limited by the lack of reporting standards for the data used to develop those models, the model architecture, and the model evaluation and validation processes. Here, we present MINIMAR (MINimum Information for Medical AI Reporting), a proposal describing the minimum information necessary to understand intended predictions, target populations, and hidden biases, and the ability to generalize these emerging technologies. We call for a standard to accurately and responsibly report on AI in health care. This will facilitate the design and implementation of these models and promote the development and use of associated clinical decision support tools, as well as manage concerns regarding accuracy and bias.

Keywords: artificial intelligence; clinical decision support; electronic health records; reporting standards.

PubMed Disclaimer

References

    1. Rothman B, Leonard JC, Vigoda MM.. Future of electronic health records: implications for decision support. Mt Sinai J Med 2012; 79 (6): 757–68. - PubMed
    1. He J, Baxter SL, Xu J, Xu J, Zhou X, Zhang K.. The practical implementation of artificial intelligence technologies in medicine. Nat Med 2019; 25 (1): 30–6. - PMC - PubMed
    1. Hannun AY, Rajpurkar P, Haghpanahi M, et al.Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network. Nat Med 2019; 25 (1): 65–9. - PMC - PubMed
    1. Schiff GD, Bates DW.. Can electronic clinical documentation help prevent diagnostic errors? N Engl J Med 2010; 362 (12): 1066–9. - PubMed
    1. Schiff GD, Volk LA, Volodarskaya M, et al.Screening for medication errors using an outlier detection system. J Am Med Inform Assoc 2017; 24 (2): 281–7. - PMC - PubMed

MeSH terms