On 29 May, Thomas Wood presented a webinar on how AI and Natural Language Processing (NLP) can transform clinical trials in the pharmaceutical industry.
During the event, Thomas talked about
Thomas Wood also discussed the Clinical Trial Risk Tool, developed by Fast Data Science for clients in the pharma industry (CTOs, trial sponsors) to be able to use NLP and AI to predict trial risk and anticipate costs.
Download the pitch deck for the Clinical Trial Risk Tool
Fast Data Science - London
Fast Data Science is a leading data science consultancy firm providing bespoke machine learning solutions for businesses of all sizes across the globe and specialising in AI in pharma. With a focus on innovation and collaboration, Fast Data Science empowers businesses to leverage the transformative power of data.
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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.
After this ruling, will tech companies move all model training to data centres that they consider “copyright safe”? Will we see a new equivalent of a “tax haven” for training AI models on copyrighted content? An “AI haven”? This article is not legal advice.
This new video explains natural language processing: what it is, how it works, and what can it do for your organisation. Natural Language Processing (NLP) is a branch of Artificial Intelligence (AI) that focuses on giving computers the ability to understand human language, combining disciplines like linguistics, computer science, and engineering.
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