Self-supervised learning in medicine and healthcare
By R. Krishnan, Pranav Rajpurkar, Eric J. Topol. Nature Biomedical Engineering, 2022
581 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Radiology, Nuclear Medicine and Imaging
View Paper: https://www.semanticscholar.org/paper/f566a4d584907adbb2691981bced2b079948d10f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Tom Goldstein
- Andrew Gordon Wilson
- Yann LeCun
- Yuandong Tian
- Micah Goldblum
- Ruslan Salakhutdinov
- Yoshua Bengio
- Hamed Pirsiavash
In Radiology, Nuclear Medicine and Imaging
Citations in the corpus
- A foundation model for generalizable disease detection from retinal images (2023, background): “The combined qualities of strong generalization capacity of representations, and high performance achieved by fine-tuned models in many downstream tasks, indicate the great potential of SSL in medical AI in which data are abundant and healthcare tasks are diverse but labels are scarce 1,8 .”
- Artificial intelligence for digital and computational pathology (2023, background): “…biases can easily be introduced owing to a multitude of factors, such as differences between the staining protocols implemented in different institutions, the use of different scanning devices, each with a particular colour response, or different sub-populations from the training and testing data…”
- A Cookbook of Self-Supervised Learning (2023, background): “SSL can be especially useful in domains such as medicine where labels are costly or the specific task can not be known a priori [Krishnan et al., 2022, Ciga et al., 2022].”
- Self-supervised learning for medical image classification: a systematic review and implementation guidelines (2023, background): “1), as well as a few narrative reviews 21,22 , the most suitable strategies and best practices for medical images have not been suf fi ciently investigated.”
- Nanomedicine-Driven Modulation of the Gut–Brain Axis: Innovative Approaches to Managing Chronic Inflammation in Alzheimer’s and Parkinson’s Disease (2025, unknown): “Applications of SSL in medical imaging, electronic health records, and RNA/DNA networks suggest its potential in expo-some research, particularly when large datasets become available [299–303].”