An algorithm may now be able to detect serious eye diseases in premature infants by assorting images, finds a new study.

‘The decision to treat retinopathy of prematurity is taken only when retinal vessels are dilated and twisted. This particular task can be done by an algorithm with more accuracy.’

What and When: A machine learning algorithm was trained to diagnose plus disease using 5,511 retinal photographs. Data were collected from July 2011 to December 2016 and analyzed from December 2016 to September 2017.




Study Measures: The algorithm to detect plus disease was tested on an independent set of 100 images against eight ROP experts.
Authors: Michael F. Chiang, M.D., Oregon Health and Science University, Portland, Jayashree Kalpathy-Cramer, Ph.D., Massachusetts General Hospital, Boston, and coauthors.
Results: The algorithm diagnosed plus disease with comparable or better accuracy than human ROP experts.
Study Limitations: Algorithms in artificial neural networks are only as good as the data on which they are trained. It is unknown how factors such as image quality, resolution, different camera systems and field of view may affect the output of these deep learning systems.
Advertisements