Publication
Predictive modelling for clinical trial completion: assessing the phase success – incorporating missing value imputation
| Summary: | 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. Imputation methods are incorporated to improve data consistency and model performance. |
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| Main Authors: | Cheng, Júlia Zhou |
| Subject: | Clinical trials Health Care Artificial Intelligence Machine Learning Methods Predictive modeling Missing value imputation |
| Year: | 2025 |
| Country: | Portugal |
| Document type: | master thesis |
| Access type: | open access |
| Associated institution: | Universidade Nova de Lisboa |
| Language: | English |
| Origin: | Repositório Institucional da UNL |
| Summary: | 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. Imputation methods are incorporated to improve data consistency and model performance. |
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Funded activities
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