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Literature DB >> 30898923

Adversarial attacks on medical machine learning.

Samuel G Finlayson¹, John D Bowers², Joichi Ito³, Jonathan L Zittrain², Andrew L Beam⁴, Isaac S Kohane¹.

Abstract

Entities: Chemical Disease Gene Species

Mesh：

Year: 2019 PMID： 30898923 DOI： 10.1126/science.aaw4399

Source DB: PubMed Journal: Science ISSN： 0036-8075 Impact factor: 47.728

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74 in total

Review 1. Deep learning in single-molecule microscopy: fundamentals, caveats, and recent developments [Invited].

Authors: Leonhard Möckl; Anish R Roy; W E Moerner
Journal: Biomed Opt Express Date: 2020-02-27 Impact factor: 3.732

2. Identifying Ethical Considerations for Machine Learning Healthcare Applications.

Authors: Danton S Char; Michael D Abràmoff; Chris Feudtner
Journal: Am J Bioeth Date: 2020-11 Impact factor: 11.229

3. Why deep-learning AIs are so easy to fool.

Authors: Douglas Heaven
Journal: Nature Date: 2019-10 Impact factor: 49.962

Review 4. Artificial Intelligence and Orthopaedics: An Introduction for Clinicians.

Authors: Thomas G Myers; Prem N Ramkumar; Benjamin F Ricciardi; Kenneth L Urish; Jens Kipper; Constantinos Ketonis
Journal: J Bone Joint Surg Am Date: 2020-05-06 Impact factor: 5.284

Review 5. Artificial Intelligence: reshaping the practice of radiological sciences in the 21st century.

Authors: Issam El Naqa; Masoom A Haider; Maryellen L Giger; Randall K Ten Haken
Journal: Br J Radiol Date: 2020-02-01 Impact factor: 3.039

6. A System-Driven Taxonomy of Attacks and Defenses in Adversarial Machine Learning.

Authors: Koosha Sadeghi; Ayan Banerjee; Sandeep K S Gupta
Journal: IEEE Trans Emerg Top Comput Intell Date: 2020-05-25

Review 7. The Future of Digital Psychiatry.

Authors: Keith Hariman; Antonio Ventriglio; Dinesh Bhugra
Journal: Curr Psychiatry Rep Date: 2019-08-13 Impact factor: 5.285