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Volume 2 Issue 10, October 2018

Volume 2 Issue 10

Explainable AI predicts blood-oxygen levels during anaesthesia

This issue highlights machine-learning algorithms that explain hypoxaemia risk under anaesthesia during surgery, that identify polyps in colonoscopy images and videos, and that predict post-surgical adverse pathology in prostate-cancer and breast-cancer tissue samples. It also highlights predictions of tumour uptake and distribution of specific therapeutic agents, and a personalized virtual-heart model for finding radio-frequency ablation targets for infarct-related tachycardia.

The cover illustrates variations in risk factors contributing to hypoxaemia under general anaesthesia, as predicted by machine learning.

See Lundberg et al.

Surgery image: LightField Studios Inc. / Alamy Stock Photo. Cover Design: Alex Wing.


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