4 Subfields of Artificial Intelligence in Surgery
In this article, Artificial Intelligence in Surgery: Promises and Perils, four core AI subfields were introduced.
Machine Learning (ML)
Natural Language Processing (NLP)
Artificial neural network (ANN)
Computer Vision (CV)
Artificial intelligence (AI) is often referred to as computer simulation of human intelligence.
AI is an interdisciplinary field that encompasses computer science, mathematics, biology, psychology, linguistics, logic, and philosophy.
The term “artificial intelligence” was coined in 1955 by John McCarthy, a professor at Dartmouth.
1. Machine learning
Machine learning (ML) allows machines to learn and make predictions by recognizing models.
ML is how machines learn.
ML outperformed logistic regression for predicting surgical site infection.
2. Natural language processing
Natural Language Processing (NLP) is a subdomain that focuses on the computer’s ability to understand human language.
NLP is the way machines understand human language.
The NLP detects adverse events and post-operative complications by identifying words and phrases in operational reports and progress notes.
3. Artificial neural network
Artificial neural networks (ANN), a subdomain of ML, are inspired by biological nervous systems.
Deep learning is the process of using multi-layer artificial neural networks to learn complex models in data.
ANN is a simulation of the human nervous system.
ANN has surpassed more traditional approaches to risk prediction (predicting the severity of pancreatitis, predicting hospital mortality after an open abdominal aortic aneurysm repair…).
4. Computer vision
Computer vision (CV) describes machine understanding of images, videos, objects, and scenes.
CV is how machines understand images and videos.
The important application of CV in surgery includes computer-assisted diagnosis, image-guided surgery, virtual colonoscopy and predictive video analysis.
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