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Intro

The definitions below were agreed upon by members of the Medical Imaging & Technology Alliance (MITA). Documents drafted, distributed, and published by MITA that contain these terms utilize them as they are defined below.

Any other person or organization is welcome to use the definitions provided in this list with proper attribution.

If you or your organization would like to suggest a new term, recommend changes to an existing term, or otherwise provide comment on the definitions in this glossary, you are welcome to do so. Send all comments to Zack Hornberger, MITA's Director of Cybersecurity & Informatics, at zhornberger@medicalimaging.org.

List of Terms

ALGORITHMS (CLUSTERING, CLASSIFICATION, REGRESSION, AND RECOMMENDATION)

A set of rules or instructions given to an AI, neural network, or other machine to help it learn on its own.

ANALYTICAL VALIDATION

The measure of the ability of a task to accurately and reliably generate the intended technical output, from the input data.

ARTIFICIAL INTELLIGENCE (AI)

A machine’s ability to make decisions and perform tasks that simulate human intelligence and behavior.

ARTIFICIAL NEURAL NETWORK (ANN)

A learning model created to act like a human brain that solves tasks that are too difficult for traditional computer systems to solve.

AUGMENTED INTELLIGENCE, also known as INTELLIGENCE AUGMENTATION (IA)

Systems that are design to enhance human capabilities. This is contrasted with Artificial Intelligence, which is intended to replicate or replace human intelligence.

BLOCKCHAIN

A decentralized, distributed and public digital ledger that is used to record transactions across many computers so that the record cannot be altered retroactively without the alteration of all subsequent blocks and the consensus of the network. This allows the participants to verify and audit transactions inexpensively.

CHATBOTS

A program that is designed to simulate a conversation with human users by communicating through text chats, voice commands, or both. They are a commonly used interface for computer programs that include AI capabilities.

CLASSIFICATION

The problem of identifying to which of a set of categories (sub-populations) a new observation belongs, on the basis of a training set of data containing observations (or instances) whose category membership is known.

CLUSTERING

Algorithms that let machines group data points or items into groups with similar characteristics.

COGNITIVE COMPUTING

A computerized model that mimics the way the human brain thinks. It involves self-learning through the use of data mining, natural language processing, and pattern recognition.

COMPUTER AIDED DETECTION (CADe)

Refers to pattern recognition software that identifies suspicious features on the image and brings them to the attention of the radiologist, in order to decrease false negative readings.

COMPUTER AIDED DIAGNOSIS (CADx)

Refers to software that analyses a radiographic finding to estimate the likelihood that the feature represents a specific disease process (e.g. benign versus malignant).

CONVOLUTIONAL NEURAL NETWORK (CNN)

A type of neural networks that identifies and makes sense of images.

CONFIDENCE INTERVAL

An interval about a point estimate that quantifies the statistical uncertainty in the true value being estimated due to variability.

CONTINUOUS LEARNING SYSTEMS (CLS)

Systems that are inherently capable of learning from the real-world data and are able to update themselves automatically over time while in public use.

DATA MINING

The examination of data sets to discover patterns from that data that can be of further use.

DEEP LEARNING

The ability for machines to autonomously mimic human thought patterns through artificial neural networks composed of cascading layers of information.

FALSE NEGATIVE

Test result that does not detect the condition when the condition is present.

FALSE POSITIVE

Test result that detects the condition when the condition is absent.

GENETIC ALGORITHM

An evolutionary algorithm based on principles of genetics and natural selection that is used to find optimal or near-optimal solutions to difficult problems that would otherwise take decades to solve.

HEURISTIC SEARCH TECHNIQUES

Support that narrows down the search to optimal solutions for a problem by eliminating options that are incorrect.

HISTORICAL CONTROL CLINICAL TRIAL

A type of clinical trial where the percentage change in disease detection and recall/workup rates is determined by comparing data before and after the implementation of CAD into a clinical practice

KNOWLEDGE ENGINEERING

Engineering focused on building knowledge-based systems, including all of the scientific, technical, and social aspects of it.

MACHINE INTELLIGENCE

An umbrella term that encompasses machine learning, deep learning and classical learning algorithms.

MACHINE LEARNING

A facet of AI that focuses on algorithms, allowing machines to learn and change without being programmed when exposed to new data.

MACHINE PERCEPTION

The ability for a system to receive and interpret data from the outside world similarly to how humans use their senses. This is typically done with attached hardware, such as sensors.

NATURAL LANGUAGE PROCESSING

A part of AI to extract and understand human language and to process it into meaning for a specified area of interest or end-user definition.

PATTERN RECOGNITION

A branch of machine learning that focuses on the recognition of patterns and regularities in data, although it is in some cases considered to be nearly synonymous with machine learning.

PRECISION

The fraction of relevant instances among the retrieved instances

REAL TIME HEALTH SYSTEMS (RTHS)

Information systems that collect and analyze real-time information from a patient; this in contrast to systems which take a patient’s blood pressure or heartrate only when they are in the doctor’s office or admitted to a hospital.

RECOMMENDATION ALGORITHMS

Algorithms that help machines suggest a choice based on its commonality with historical data.

RECURRENT NEURAL NETWORK (RNN)

A type of neural network that makes sense of sequential information and recognizes patterns, and creates outputs based on those calculations

REGRESSION

A statistical approach that helps predict future outcomes or items in a continuous data set by solving for the pattern of past inputs, such as linear regression in statistics. Regression is foundational to machine learning and artificial intelligence.

REINFORCEMENT LEARNING

A type of machine learning where algorithms are trained through interactions with an environment. When an algorithm’s processes deliver desired results, it receives positive feedback. For example, the algorithm receives a reward for scoring a point or winning a game.

RELEVANCE

The concept of one topic being connected to another topic in a way that makes it useful to consider the second topic when considering the first.

SEQUENTIAL READ CLINICAL TRIAL

A clinical trial where the exam is first read prior to, and then following, CAD input. The change in disease detection due to the CAD input, as well as the change in the recall/workup rates, will determine the contribution of CAD to patient management. Importantly, the percentage increase in disease detection should be concordant with, or less than, the percentage increase in the recall/workup rates.

SUPERVISED MACHINE LEARNING

The machine learning task of learning a function that maps an input to an output based on example input-output pairs. It infers a function from labeled training data consisting of a set of training examples

TRUE NEGATIVE

Test result that does not detect the condition when the condition is absent.

TRUE POSITIVE

Test result that detects the condition when the condition is present.