[Skip to Navigation]
Invited Commentary
August 6, 2020

Deep Learning Algorithms and the Protection of Data Privacy

Author Affiliations
  • 1School of Engineering, University of Melbourne, Parkville, Victoria, Australia
  • 2Centre for AgriBioscience, AgriBio, Bundoora, Victoria, Australia
  • 3Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia
  • 4Department of Surgery, Ophthalmology, University of Melbourne, Victoria, Australia
JAMA Ophthalmol. 2020;138(10):1024-1025. doi:10.1001/jamaophthalmol.2020.2766

The application of artificial intelligence to pattern recognition in medicine has been described in recent studies in machine learning.1 In particular, the use of machine learning in the form of the convolutional neural network has underpinned the current popularity of so-called deep learning algorithms, which are essentially convolutional neural network models distinguished by having a large number of hidden layers with many adjustable parameters requiring a large quantity of data for training. A deep learning algorithm can be applied to raw data without the need for data normalization and can be used to extract the inherent nonobvious features from training images that are necessary for accurate discrimination.1,2

Limit 200 characters
Limit 25 characters
Conflicts of Interest Disclosure

Identify all potential conflicts of interest that might be relevant to your comment.

Conflicts of interest comprise financial interests, activities, and relationships within the past 3 years including but not limited to employment, affiliation, grants or funding, consultancies, honoraria or payment, speaker's bureaus, stock ownership or options, expert testimony, royalties, donation of medical equipment, or patents planned, pending, or issued.

Err on the side of full disclosure.

If you have no conflicts of interest, check "No potential conflicts of interest" in the box below. The information will be posted with your response.

Not all submitted comments are published. Please see our commenting policy for details.

Limit 140 characters
Limit 3600 characters or approximately 600 words