
I am a pediatric cardiologist and have cared for children with heart disease for the past three decades. In addition, I have an educational background in business and finance as well as healthcare administration and global health – I gained a Masters Degree in Public Health from UCLA and taught Global Health there after I completed the program.
“The neural network is this kind of technology that is not an algorithm, it is a network that has weights on it, and you can adjust the weights so that it learns. You teach it through trials.”
Howard Rheingold, American critic and writer
At a recent American Board of AI in Medicine (ABAIM) course, an attendee asked a simple yet complicated question:
“Is deep learning considered a supervised or unsupervised learning?”
Deep learning involves the use of complex models that exceed the capabilities of machine learning tools such as logistic regression and support vector machines, but these deep learning models are essentially “function approximators”.
Deep learning uses supervised learning in situations such as image classification or object detection, as the network is used to predict a label or a number (the input and the output are both known). As the labels of the images are known, the network is used to reduce the error rate, so it is “supervised”.
Neural networks, on the other hand, can also be used to cluster images based on similarities. One can extract the features with a neural network, then deploy an unsupervised methodology such as k-means clustering. A neural network can be in the form of a semi-supervised deep neural network.
In addition, autoencoders are neural nets that can be used for image compression and reconstruction via a latent space representation of compressed data; in short, it outputs whatever is inputted. These autoencoders are considered self-supervised learning neural nets.
Finally, reinforcement learning with neural networks can be used, and was the methodology behind DeepMind and its victory in the game Go.
Therefore, deep learning can be supervised, unsupervised, semi-supervised, self-supervised, or reinforcement, and it depends mostly on how the neural network is used.
We are very excited to welcome you to attend in-person the AIMed Global Summit taking place January 18th-20th, 2022, at the sublime Ritz-Carlton resort in Laguna Niguel, southern California. This summit promises to be the most exciting yet, with Drs. Eric Topol and Daniel Kraft among the keynote speakers. We are all very much looking forward to seeing and learning from each other in person for human-to-human conversations and networking at this event. Book your place now.