How Can AI Be Used in Clinical Trials? Clinical trials are essential for developing new drugs and therapies, but they are often slow, costly, and complex. The traditional process involves recruiting participants, managing extensive data, ensuring regulatory compliance, and analyzing outcomes—all of which can take years and significant resources. Artificial Intelligence (AI) is transforming clinical trials by making them faster, more efficient, and more accurate. AI algorithms can quickly analyze electronic health records (EHRs) to identify eligible participants, significantly reducing recruitment time and costs. During the trial, AI can monitor patients in real-time, using wearable devices and mobile apps to continuously collect data, detect adverse events early, and enhance patient safety.
Our NLP research has been published in BMC Psychiatry! Fast Data Science has been working on the Harmony project in collaboration with UCL, Ulster University, and Universidade Federal de Santa Maria. Harmony is an open-source natural language processing tool designed to revolutionise mental health research as well as an AI research project.
AI in science and research Artificial intelligence (AI) has emerged as a revolutionary force in science and research, transforming how we approach, analyze, and interpret data. The integration of AI technologies into scientific research has opened up new avenues for discovery, significantly improving efficiency, accuracy, and scope of research activities. In this blog, we will explore the various ways AI is being utilized in science and research, along with some comparative analytics to highlight its growing impact.
Above: video of Thomas Wood presenting Harmony at the Pydata on 27 March 2024
Generative AI Introduction Generative AI, a subset of AI, is fundamentally transforming industries and shaping the future. Leveraging advanced algorithms, generative AI can create content, designs, and solutions that were previously unimaginable. By using machine learning models such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), generative AI systems can produce new data that mimics the patterns and structures of the training data.
Big Data The emergence of big data has revolutionized industries, transforming traditional business models and decision-making processes. In this comprehensive exploration, we delve into what big data is, its significant impacts on business strategy, and how companies can leverage vast datasets to drive innovation and competitive advantage.
AI in Finance The integration of artificial intelligence (AI) into the finance sector has revolutionized how institutions operate, from automating operations to enhancing customer engagement and improving risk management. This comprehensive exploration will delve into several key areas where AI is making significant inroads within the industry.
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