Master's Thesis
Utilising Large Pretrained Language Models for Configuration and Support of a Clinical Information System
Final Thesis 960.3 kBAuthor of thesis: Ing. Michal Sova
Acad. year: 2023/2024
Supervisor: RNDr. Marek Rychlý, Ph.D.
Reviewer: doc. Ing. Radek Burget, Ph.D.
Abstract:The aim of this work is to get acquainted with the essence and use of large pre-trained language models, to get acquainted with the configuration options of the clinical information system FONS Enterprise and the possibility of its adaptation to the specific environment of customers. The work first presents large pre-trained language models and the FONS Enterprise clinical information system. This work examines possibilities of training models and implementing RAG methods on data from the clinical system. The implementation of the RAG architecture is supported by the tools LangChain and LlamaIndex. The results show that the RAG method with the Gemma model and the bge-m3 embedding model provides the most relevant answers on basic questions, but struggles to understand more complex questions. The method of pre-training the model does not produce the expected results, even after adjusting the training parameters.
clinical information system, large language models, RAG architecture, pre-training, Llama, Gemma, Mistral, LangChain, LlamaIndex
Date of defence
18.06.2024
Result of the defence
Defended (thesis was successfully defended)
Grading
D
Process of defence
Student nejprve prezentoval výsledky, kterých dosáhl v rámci své práce. Komise se poté seznámila s hodnocením vedoucího a posudkem oponenta práce. Student následně odpověděl na otázky oponenta a na další otázky přítomných. Komise se na základě posudku oponenta, hodnocení vedoucího, přednesené prezentace a odpovědí studenta na položené otázky rozhodla práci hodnotit stupněm D.
Topics for thesis defence
- Bylo v praktické aplikaci nakonec využito vektorové úložiště zmiňované v kapitole 5.2.2? Pokud ano, jaké a jakým způsobem?
- Jak probíhalo ověřování Vašeho řešení?
Language of thesis
Czech
Faculty
Department
Study programme
Information Technology and Artificial Intelligence (MITAI)
Specialization
Intelligent Systems (NISY)
Composition of Committee
doc. Ing. Vladimír Janoušek, Ph.D. (předseda)
prof. Ing. Jiří Jaroš, Ph.D. (člen)
Ing. Jaroslav Rozman, Ph.D. (člen)
Ing. Vojtěch Mrázek, Ph.D. (člen)
Ing. Martin Hrubý, Ph.D. (člen)
Ing. Radek Kočí, Ph.D. (člen)
Supervisor’s report
RNDr. Marek Rychlý, Ph.D.
Grade proposed by supervisor: C
Reviewer’s report
doc. Ing. Radek Burget, Ph.D.
Grade proposed by reviewer: C