Introduction to Artificial Intelligence in Healthcare

Flashcards covering fundamental concepts and terminology related to Artificial Intelligence and its applications in healthcare.

Artificial Intelligence (AI)

A multidisciplinary field of computer science focused on creating systems capable of tasks that usually require human intelligence.

Narrow AI (Weak AI)

AI systems designed to perform specific tasks; they are specialized and do not generalize beyond their programming.

General AI (Strong AI)

A theoretical AI that can understand and apply knowledge across a broad range of tasks, similar to human cognitive abilities.

Superintelligent AI

AI systems that surpass human intelligence across all domains, including creativity, problem-solving, and moral reasoning.

Machine Learning

A subset of AI that enables systems to learn from data and improve their performance without being explicitly programmed.

Natural Language Processing (NLP)

A branch of AI that enables machines to understand and interpret human language.

Predictive Analytics

The use of statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data.

Self-Driving Cars

Autonomous vehicles that use AI, sensors, and algorithms to navigate and operate without human intervention.

Medical Diagnostics

AI systems that analyze medical images to detect conditions such as fractures, tumors, or pneumonia.

Reinforcement Learning

A type of machine learning where an agent learns to make decisions by receiving feedback in the form of rewards or penalties.

Semi-Supervised Learning

A mix of labeled and unlabeled data used to train AI models, leveraging the advantages of both supervised and unsupervised learning.

Decision Trees

A tree-like model used to make decisions based on certain conditions that leads to a prediction or classification.

Neural Networks

Computational models inspired by the human brain that learn complex patterns through layers of interconnected nodes.

Fuzzy Logic Systems

AI systems that handle reasoning with uncertainty and approximate reasoning rather than fixed and exact values.

Generative Adversarial Networks (GANs)

A class of generative models where two networks compete to produce realistic data samples.

Clinical Decision Support Systems (CDSS)

AI systems designed to support clinical decision-making by analyzing patient data and suggesting treatment options.

Telemedicine

The use of AI and digital information technologies to provide healthcare services remotely.

Wearable Technology

Devices like smartwatches that monitor health metrics and provide real-time health data analytics.

AI-powered Chatbots

Virtual assistants that use AI to interact with users, providing health information or managing appointments.

Drug Discovery

The process of identifying new candidate medications using AI to predict the effectiveness of compounds.