Must-Know AI Jargon

for Medical Professionals

A comprehensive guide to artificial intelligence terminology with practical medical examples

AI TermDefinitionMedical Example
Artificial Intelligence (AI)
Core Concept
Simulating human intelligence using machines
Chatbots answering patient queries 24/7
Machine Learning (ML)
Technique
Algorithms that learn patterns from data without being explicitly programmed
Predicting hospital readmission based on EHR data
Deep Learning (DL)
Advanced
Subset of ML using neural networks with many layers
Identifying diabetic retinopathy from retinal images
Neural Network
Architecture
A series of algorithms mimicking the human brain
Classifying ECG signals as normal or abnormal
Natural Language Processing (NLP)
Technique
Understanding and generating human language by machines
Extracting symptoms from free-text clinical notes
Large Language Model (LLM)
Core Technology
A type of NLP model trained on large text datasets
Summarizing lengthy medical literature or guidelines
Supervised Learning
Technique
ML with labeled data
Training a model to detect pneumonia using chest X-rays labeled by radiologists
Unsupervised Learning
Technique
ML with unlabeled data
Discovering unknown disease subtypes from genetic data
Reinforcement Learning
Technique
Learning via trial-and-error to maximize reward
Optimizing personalized drug dosage in ICU settings
Overfitting
Challenge
Model performs well on training data but poorly on new data
AI model diagnoses rare disease well in training set but fails on real patients
Bias
Challenge
Systematic error due to non-representative data
Model underperforms on minority populations due to training data imbalance
Explainability
Approach
Ability to understand AI model's decision-making
Showing which clinical features led to a sepsis alert
Synthetic Data
Approach
Artificially generated data that mimics real patient data
Generating realistic but fake EHRs for AI training without privacy risks
13 AI termsFor medical professionals