Find out how ACRC Researchers delve into the field of artificial intelligence. Artificial Intelligence (AI) plays a crucial role in today's world by driving innovation and efficiency across various sectors. It enhances decision-making through data analysis and has the potential to revolutionise healthcare with predictive diagnostics and personalised medicine. The importance of AI can be understated within the ACRC, as it is a theme that was woven among almost all our work packages during our research phase. Below, you can see some of the areas where aspects of AI have been investigated by our researchers: Clinical Coding Clinical coding is the process of assigning standardised codes for an interaction with the health service (a visit to GP or a hospital stay). Such ‘coded’ information is widely used for patient care, auditing and research. Clinical coding task is a resource-intensive process which requires a group of specialised clinical coders to manually conduct systematic code assignments for multi-source, multi-modal raw medical records based on standard coding classification systems consisting of thousands of candidate codes. You can read a case study, here. Unobtrusive Video Monitoring AnalysisThe Unobtrusive Video Monitoring Analysis team has been investigating how video analysis methods might be usable in supporting ageing adults living in their own homes.People are naturally anxious about being videoed in their own homes so the approach that we have taken is based on extracting a '3D skeleton' description of the observed person, and then immediately discarding the original video. This process avoids recording the appearance of the monitored person (who were shown the skeletons), thus preserving privacy while still acquiring rich data for several different types of monitoring.You can find out more, here. Identifying patterns in the use of multiple medicationsIn an ageing world people are increasingly living with multiple long term health conditions, and consequently are being prescribed multiple medications more often. Taking multiple medications concurrently, also known as polypharmacy, is associated with several negative impacts such as increased risk of adverse side effects, increased risk of drug-drug interactions, and reduced adherence to prescription instructions. Historically, discussion around polypharmacy has centred around the number of drugs a person is taking. However, other authors have emphasized the need to broaden the focus to other aspects of polypharmacy; highlighting that in some cases many concurrent drugs are appropriate and provide benefits that outweigh the risks.This work proposed a new, probabilistic, clustering model which can identify profiles of prescription patterns based on four key aspects of each medication for individuals in that cluster.Find out more, here. Scottish AI AllianceACRC Researchers have worked closely to the Scottish AI Alliance to take our research forwards.The Scottish AI Alliance is a partnership between The Data Lab and the Scottish Government and is led by a Minister-appointed Chair and overseen by Senior Responsible Officers from The Data Lab (CEO) and the Scottish Government (CDO). The Scottish AI Alliance is tasked with the delivery of the vision outlined in Scotland’s AI Strategy in an open, transparent and collaborative way.Scottish AI PlaybookScottish AI RegisterLiving with AIScottish AI Summit This article was published on 2025-08-18
