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Machine learning modeling practices to support the principles of AI and ethics in nutrition research

Health and Fitness

Machine learning modeling practices to support the principles of AI and ethics in nutrition research

D. M. Thomas, S. Kleinberg, et al.

Discover how nutrition research can leverage AI and machine learning while adhering to ethical modeling practices. This tutorial by Diana M. Thomas, Samantha Kleinberg, and others unveils essential guidelines for developing AI/ML models in nutrition, ensuring robust and reproducible outcomes.

00:00
Playback language: English
Abstract
Nutrition research increasingly utilizes artificial intelligence (AI) and machine learning (ML) models. However, inadequate modeling processes can lead to misleading results and ethical concerns. This tutorial identifies frequently omitted best practices in statistical modeling and their application to ML models in nutrition research. It provides a checklist and guiding principles to help nutrition researchers develop, evaluate, and implement AI/ML models ethically and effectively, mitigating potential bias and ensuring reproducible results.
Publisher
Nutrition and Diabetes
Published On
Dec 02, 2022
Authors
Diana M. Thomas, Samantha Kleinberg, Andrew W. Brown, Mason Crow, Nathaniel D. Bastian, Nicholas Reisweber, Robert Lasater, Thomas Kendall, Patrick Shafto, Raymond Blaine, Sarah Smith, Daniel Ruiz, Christopher Morrell, Nicholas Clark
Tags
nutrition research
artificial intelligence
machine learning
ethical modeling
best practices

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