We are excited to introduce the new Harmony Meta platform, which we have developed over the past year. Harmony Meta connects many of the existing study catalogues and registers.
Guest post by Jay Dugad Artificial intelligence has become one of the most talked-about forces shaping modern healthcare. Machines detecting disease, systems predicting patient deterioration, and algorithms recommending personalised treatments all once sounded like science fiction but now sit inside hospitals, research labs, and GP practices across the world.
If you are developing an application that needs to interpret free-text medical notes, you might be interested in getting the best possible performance by using OpenAI, Gemini, Claude, or another large language model. But to do that, you would need to send sensitive data, such as personal healthcare data, into the third party LLM. Is this allowed?
How can you use generative AI to find topics in a free text survey and identify the commonest mentioned topics? Imagine that you work for a market research company, and you’ve just run an online survey. You’ve received 10,000 free text responses from users in different languages. You want to quickly make a pie chart or bar chart showing common customer complaints, broken down by old customers, new customers, different locations, different spending patterns, and demographics.
When can lawyers, litigants in person, and expert witnesses use AI in court documents? In the last few years in the UK, the USA, Canada, Ireland and other jurisdictions, cases have been reported where submissions were made to a court where the author of a document used generative AI tools such as ChatGPT to create those documents. This has wasted court time, resulted in submissions being rejected or even resulted in changes to cost awards.
A person has recently returned from a camping trip and has a fever. Should a doctor diagnose flu or Lyme disease? Would this be any different if they had not mentioned their camping trip? Here’s how LLMs differ from human experts.
How can you predict customer churn using machine learning and AI? In an earlier blog post, I introduced the concept of customer churn. Here, I’d like to dive into customer churn prediction in more detail and show how we can easily and simply use AI to predict customer churn.
A generative AI-based legal advice tool for small businesses in distress We are pleased to announce the publication of our paper A generative AI-based legal advice tool for small businesses in distress, in collaboration with an interdisciplinary team based in the UK and Hungary.
Thomas Wood presents the Clinical Trial Risk Tool before the November meeting of the Clinical AI Interest Group at Alan Turing Institute The Clinical AI Interest group is a community of health professionals from a broad range of backgrounds with an interest in Clinical AI, organised by the Alan Turing Institute.
Fast Data Science will appear at Ireland’s Expert Witness Conference on 20 May 2026 in Dublin On 20 May 2026, La Touche Training is running the Expert Witness Conference 2026, at the Radisson Blu Hotel, Golden Lane, Dublin 8, Ireland. This is a full-day event combining practical workshops and interactive sessions, aimed at expert witnesses and legal professionals who want to enhance their expertise. The agenda covers critical topics like recent developments in case law, guidance on report writing, and techniques for handling cross-examination.
What we can do for you
