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Predictive modelling for clinical trial completion: assessing the phase success - incorporating RAG techniques for predictive modelling of clinical trial outcomes

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Resumo:This study investigates predictive modeling of clinical trial completion using the HINTBasic and HINTPlus models. By integrating multimodal datasets, the models predict clinical trial phase success. It provides interpretability insights into the HINTPlus model's decision-making process. Retrieval-Augmented-Generation techniques were used to contextualize results. Our findings support informed decision-making, optimize resource allocation, and accelerate drug development in clinical trials.
Autores principais:Hamrouni, Jasmin
Assunto:Clinical trials Health care Artificial Intelligence Machine learning methods Predictive modelling Model interpretability Contextuality Retrieval-Augmented Generation
Ano:2025
País:Portugal
Tipo de documento:dissertação de mestrado
Tipo de acesso:acesso aberto
Instituição associada:Universidade Nova de Lisboa
Idioma:inglês
Origem:Repositório Institucional da UNL

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