Find out how AI and natural language processing are being used in mental health research and other areas of social sciences research.
Here’s a series of interviews with the Wellcome Trust about the Mental Health Data Prize. Members of the three winning teams are discussing the prize and the transformative potential of data in mental health science. Thomas Wood at Fast Data Science talks about the Harmony project, funded by the Wellcome Trust and now by ESRC: Economic and Social Research Council.
Harmonise questionnaire items
Harmony’s team consists of Bettina Moltrecht at UCL, Eoin McElroy at Ulster University, Thomas Wood at Fast Data Science, Mauricio Scopel Hoffman at Universidade Federal de Santa Maria, John Rogers at Delosis, and Rachel Holland Gomes.
You may want to take a look at our paper recently published in BMC Psychiatry:
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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.
Guest post by Alex Nikic In the past few years, Generative AI technology has advanced rapidly, and businesses are increasingly adopting it for a variety of tasks. While GenAI excels at tasks such as document summarisation, question answering, and content generation, it lacks the ability to provide reliable forecasts for future events. GenAI models are not designed for forecasting, and along with the tendancy to hallucinate information, the output of these models should not be trusted when planning key business decisions. For more details, a previous article on our blog explores in-depth the trade-offs of GenAI vs Traditional Machine Learning approaches.
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