# Anesthesiologist-level forecasting of hypoxemia with only SpO2 data using deep learning

arXiv: https://arxiv.org/abs/1712.00563 · HTML: https://mlsanity.com/paper/1712.00563/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Dec 2017.

## Built on by (most cited first, 1 of 1)

- [Predicting Intraoperative Hypoxemia with Hybrid Inference Sequence Autoencoder Networks](https://mlsanity.com/paper/2104.14756/) (2021)

## Abstract (arXiv)

We use a deep learning model trained only on a patient's blood oxygenation data (measurable with an inexpensive fingertip sensor) to predict impending hypoxemia (low blood oxygen) more accurately than trained anesthesiologists with access to all the data recorded in a modern operating room. We also provide a simple way to visualize the reason why a patient's risk is low or high by assigning weight to the patient's past blood oxygen values. This work has the potential to provide cutting-edge clinical decision support in low-resource settings, where rates of surgical complication and death are substantially greater than in high-resource areas.