Medical Information and Artificial Intelligence Systems

Generative Artificial Intelligence (AI), based on large language models, neural networks, and transformers, demonstrates remarkable capabilities in analyzing vast amounts of data, writing texts, and generating images, audio, and video. Its application has radically transformed how information is searched, retrieved, and synthesized from electronic sources, the internet, books, scientific journals, news bulletins, social networks, blogs, personal and corporate websites, and bibliographic databases.

While searching for medical and broader healthcare information on the World Wide Web has been commonplace over the last two decades, for the first time, the validation, evaluation, and logical processing of available information does not rely solely on humans. The automated, algorithmic, and statistical manner in which generative AI models analyze verbal, visual, or audio content carries the risk of forming extreme hypotheses, drawing false or unsubstantiated conclusions, and projecting remote or marginal correlations. This lecture examines the available AI tools and their applications within the context of medical information, targeting both the general public and healthcare professionals.

Artemis Chaleplioglou is an Assistant Professor at the Department of Archival, Library and Information Studies of the University of West Attica, specializing in “Library Science with an emphasis on Biomedical Information.” Her field of expertise focuses on the management, organization, documentation, and dissemination of biomedical data and information, library and information science, as well as bibliographic and bibliometric analysis.

Her scientific research has been published in international peer-reviewed journals in the fields of information science and computer science.