# Active Informed Consent to Boost the Application of Machine Learning in Medicine

arXiv: https://arxiv.org/abs/2210.08987 · HTML: https://mlsanity.com/paper/2210.08987/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 33 references that are in the map.
- First posted on arXiv 27 Sep 2022.

## Builds on (most cited first, 3 of 3)

- [Human-in-the-loop Artificial Intelligence](https://mlsanity.com/paper/1710.08191/) (2017)
- [A Gentle Introduction to Deep Learning in Medical Image Processing](https://mlsanity.com/paper/1810.05401/) (2018)
- [Radiological images and machine learning: trends, perspectives, and prospects](https://mlsanity.com/paper/1903.11726/) (2019)

## Abstract (arXiv)

Machine Learning may push research in precision medicine to unprecedented heights. To succeed, machine learning needs a large amount of data, often including personal data. Therefore, machine learning applied to precision medicine is on a cliff edge: if it does not learn to fly, it will deeply fall down. In this paper, we present Active Informed Consent (AIC) as a novel hybrid legal-technological tool to foster the gathering of a large amount of data for machine learning. We carefully analyzed the compliance of this technological tool to the legal intricacies protecting the privacy of European Citizens.