Multi‐center machine learning in imaging psychiatry: A meta‐model approach

By Petr Dluhos, Daniel Schwarz, Wiepke Cahn, N. V. Haren, René S. Kahn, F. Španiel, J. Horáček, T. Kašpárek, H. Schnack. 2017

47 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

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

1. Jayashree Kalpathy-Cramer
2. Daniel L. Rubin
3. James M. Brown
4. Bruce R. Rosen
5. Ken Chang
6. Andrew L Beers
7. Carson K. Lam
8. Darvin Yi

In Cognitive Neuroscience

1. Daniel L. Rubin

In Radiology, Nuclear Medicine and Imaging

1. Daniel L. Rubin
2. Bruce R. Rosen
3. Carson K. Lam
4. Darvin Yi

Citations in the corpus

• Distributed deep learning networks among institutions for medical imaging (2018, background): “However, patient sample sizes are often small, especially for rarer diseases.(9) Small sample sizes may result in a neural network model with low generalizability.”