[apologize for multiple postings] The THIRD seminar of the "AI & Health" series as hosted by HC@AIxIA, i.e., the "Artificial Intelligence for Healthcare" working group of the Italian Association for Artificial Intelligence, is announced. *Save the date: 8 March.* We hope you will attend and participate in the discussion on the relevant topics that will be presented and by our speakers. *Feel free to share this with those potentially interested.* Please find some details below. All directions for participating are available at https://aixia.it/gruppi/hc/. *== Are you interested in Joining the group? ==* Please head to https://aixia.it/en/gruppi/hc/ fo find out how. Do not hesitate to contact us at hc-aixia@googlegroups.com for any information or clarification. Thank you for your interest in the AI & Health seminar series and the HC@AIxIA working group, and see you soon! Sincerely, Francesco Calimeri, Mauro Dragoni, Fabio Stella (coordinators of the HC@AIxIA working group) *== March 2024 seminar ==* *Link to participate*: https://unimib.webex.com/unimib/j.php?MTID=m42fa53368d1f644d66bb75fbd173b7dc *2024 MARCH 8 - 4:30PM CET* *Andrea Palladino and Margherita Bodini* GSK (Siena, Italy) *Title*: Natural language processing and deep learning for genome classification *Abstract*: Machine learning classification of entire genome sequences would find many important applications in the bacteriology field. Among the most relevant, there are population genomics, antibiotic resistance monitoring, and outbreak investigation. Despite the prosperous application of AI to genetic sequences, especially in eukaryotes (Y. Ji et al. Bioinformatics (2021), Z. Avsec et al., Nature Methods (2021)), it is still challenging to use machine learning on the complete genome sequence of an organism. In this seminar we will show various approaches to apply Natural Language Processing (NLP) to biological sequences. We will guide attendants in understanding the relevance and some details of such methods and show practical examples of application to Neisseria meningitidis genome. We will describe our recent work on the classification of B/non-B capsules and on the identification of strains that colonize asymptomatically the nasopharynx (carrier) from those that cause meningitis or sepsis (disease), comparing with the state of the art methodology. Finally, we will show how deep learning can be applied to the same scopes, with practical examples. *Short Bio*: Andrea Palladino is a physicist by formation, working in the field of artificial intelligence since 2020. He is senior data scientist at GSK in the group of systems vaccinology, applying machine learning algorithms to human data in the context of immuno-senescence, to investigate the relationship between chronological age and "age” of the immune system. *Short Bio*: Margherita Bodini is a Bioinformatician, with PhD in computational biology at the University of Milan. She works as senior data scientist at GSK in the group of bacterial computational genomics, applying genomic data analysis and machine learning towards research, development, and life cycle management of vaccine products.