Review on multi-modal AI models to integrate imaging and omics data
| dc.rights.license | CC-BY-NC-ND | |
| dc.contributor | Wilson Silva | |
| dc.contributor.advisor | Santos Silva, W.J. dos | |
| dc.contributor.author | Vincenzo, Matteo Di | |
| dc.date.accessioned | 2024-02-29T01:01:36Z | |
| dc.date.available | 2024-02-29T01:01:36Z | |
| dc.date.issued | 2024 | |
| dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/46086 | |
| dc.description.sponsorship | Utrecht University | |
| dc.language.iso | EN | |
| dc.subject | This review evaluates the utilization of multi-modal artificial intelligence (AI) techniques for merging multi-omics and imaging data in healthcare. It examines diverse models and their performance in predicting patient recovery and treatment outcomes. | |
| dc.title | Review on multi-modal AI models to integrate imaging and omics data | |
| dc.type.content | Master Thesis | |
| dc.rights.accessrights | Open Access | |
| dc.subject.courseuu | Bioinformatics and Biocomplexity | |
| dc.thesis.id | 28586 |