AI TERMS & ACRONYMS EXPLAINED
There is a lot of jargon in data science and AI, so we’ve created this list for non-specialists who want to find out more about these topics without the technical language. We also hope it will be a useful resource for researchers in areas that intersect with data science and AI.
This is an ongoing project, so we will regularly be reviewing the list of terms and definitions.
If you have a smartphone or have used the internet to search for something – AI is working in the background to help you get what you are looking for.
We use AI to find patterns in very large datasets. With so much data it’s hard for humans to see what is going on and detect useful patterns. AI makes it easier to spot these patterns.
Using the collective expertise of patients, clinicians, researchers and artificial intelligence to improve the care of people who live with many health conditions medicines.
Any information that has been collected for analysis or reference.
Data can take the form of numbers and statistics, text, symbols, or multimedia such as images, videos, sounds and maps.
Data that has been collected but not yet processed, cleaned or analysed is known as ‘raw’ or ‘primary’ data.
This is an umbrella term for any field of research that involves the processing of large amounts of data in order to provide insights into real-world problems.
Data scientists are a diverse tribe, ranging from engineers, medics and climatologists to ethicists, economists and linguists.
These are used in general practice (by your GP) and in hospitals to record information about diagnoses and treatments.
In this research we will only ever use anonymised records to make sure we cannot identify individuals
This refers to over 230 different illnesses like heart problems, cancer, dementia, mental health problems, and long-term infectious diseases like HIV or hepatitis.
This is a subfield of AI that uses algorithms trained on data sets to create models that enable machines to perform tasks that would otherwise only be possible for humans, such as categorising images, analysing data or predicting fluctuations.
It imitates the way that humans learn, gradually improving its accuracy.
The co-existence of two or more chronic conditions (physical or mental) in a person in medical and research circles.
This has often been referred to as ‘multimorbidity’.
When members of the public use their view and personal experience of illness and treatment to help to prioritise, plan, deliver, evaluate and share health and social care research.
A Secure Data Environment (SDE) is a protected space for sensitive data that can only be accessed by authorized researchers remotely.
It upholds the highest standards of privacy and security for health and social care data used in research and analysis.
A public organisation that funds research and innovation in the UK.
The UKRI Medical Research Council Strategic Priorities Fund is an £830 million investment in multi- and interdisciplinary research supporting a number of projects working in parallel with AI MULTIPLY:
- MumPreDiCT
- ADMISSION
- GEMINI








