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Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-09202023-191932


Tipo di tesi
Tesi di laurea magistrale
Autore
BANDONI, JACOPO
URN
etd-09202023-191932
Titolo
Evidence-based question answering for biomedical research
Dipartimento
INFORMATICA
Corso di studi
INFORMATICA
Relatori
relatore Priami, Corrado
Parole chiave
  • biomedical research
  • deep learning
  • generative search engine
  • language model
  • question answering
Data inizio appello
06/10/2023
Consultabilità
Non consultabile
Data di rilascio
06/10/2063
Riassunto
This master thesis aims to develop an evidence-based question-answering system for biomedical research in collaboration with Bayer pharmaceutical. The research focuses on addressing challenges such as retrieving relevant information, customization, privacy, and efficiency. The proposed system leverages natural language processing techniques and large language models to enable users to ask questions in an intuitive manner and receive accurate, informative answers. The study explores the feasibility of constructing a generative search engine for scientific literature and investigates the potential of transferring the capabilities of a large language model to a smaller, more privacy-conscious model while maintaining comparable performance.
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