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