Publicação
Predictive modeling for clinical trial completion: assessing the phase success - factors driving predictive outcomes
| datacite.subject.fos | Ciências Sociais::Economia e Gestão | |
| dc.contributor.advisor | Han, Qiwei | |
| dc.contributor.author | Francalanci, Erica | |
| dc.date.accessioned | 2026-03-31T13:30:10Z | |
| dc.date.available | 2026-03-31T13:30:10Z | |
| dc.date.issued | 2025-07-15 | |
| dc.date.submitted | 2024-12-17 | |
| dc.description.abstract | 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. Additionally, the study provides interpretability insights into the HINTPlus model's decision-making process. Our findings support informed decision-making, optimize resource allocation, and accelerate drug development in clinical trials. | eng |
| dc.identifier.tid | 204133742 | |
| dc.identifier.uri | http://hdl.handle.net/10362/201960 | |
| dc.language.iso | eng | |
| dc.relation | UID/ECO/00124/2013 | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Clinical trials | |
| dc.subject | Health care | |
| dc.subject | Artificial intelligence | |
| dc.subject | Machine learning methods | |
| dc.subject | Predictive modeling | |
| dc.subject | Model interpretability | |
| dc.subject | Selective classification | |
| dc.title | Predictive modeling for clinical trial completion: assessing the phase success - factors driving predictive outcomes | eng |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| thesis.degree.name | A Work Project, presented as part of the requirements for the Award of a Master’s degree in Business Analytics from the Nova School of Business and Economics |