Deep Reinforcement Learning in Medicine

Kidney Diseases
Anders Jonsson

Abstract

Reinforcement learning has achieved tremendous success in recent years, notably in complex games such as Atari, Go, and chess. In large part, this success has been made possible by powerful function approximation methods in the form of deep neural networks. The objective of this paper is to introduce the basic concepts of reinforcement learning, explain how reinforcement learning can be effectively combined with deep learning, and explore how deep reinforcement learning could be useful in a medical context.

References

Sep 5, 2009·International Journal of Neural Systems·Joelle PineauMassimo Avoli
Aug 6, 2014·Artificial Intelligence in Medicine·Pablo Escandell-MonteroJosé D Martín-Guerrero
Feb 27, 2015·Nature·Volodymyr MnihDemis Hassabis
Jan 29, 2016·Nature·David SilverDemis Hassabis
Oct 21, 2017·Nature·David SilverDemis Hassabis
Mar 21, 2018·Healthcare Informatics : the Business Magazine for Information and Communication Systems·Ying LiuYanzhi Wang

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Citations

Jan 9, 2021·Medical & Biological Engineering & Computing·Katharine NowakowskiTien-Tuan Dao
Mar 7, 2021·Journal of Clinical Medicine·Ljiljana Trtica MajnarićAndreas Holzinger
May 13, 2021·Pediatric Radiology·Sudhen B DesaiMatthew P Lungren
Aug 12, 2021·Computational and Structural Biotechnology Journal·Raihan RafiqueJulhash U Kazi
Sep 3, 2021·Scientific Reports·Sung Ho KangSang-Hwy Lee
Mar 1, 2019·Kidney Diseases·Miguel Hueso, Alfredo Vellido
Dec 28, 2021·The American Surgeon·Mert Marcel DagliCharles E Butler

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