Prediction of breast cancer Invasive Disease Events using transfer learning on clinical data as image-form
This is the first study proposing an approach which converts clinical information into an image-form to develop a decision support system for identifying patients at high risk of occurrence of an Invasive Disease Event, and then defining personalized oncological therapeutic treatments for breast cancer patients.
Authors
- Maria Colomba Comes (ORCID: https://orcid.org/0000-0003-2903-4389)
- Annarita Fanizzi (ORCID: https://orcid.org/0000-0002-2729-9896)
- Annalisa Nardone (ORCID: https://orcid.org/0000-0003-0679-2435)
- Agnese Latorre (ORCID: https://orcid.org/0000-0003-0108-0113)
- Samantha Bove (ORCID: https://orcid.org/0000-0001-7772-7513)
- Alessandro Rizzo (ORCID: https://orcid.org/0000-0003-1990-0490)
- Clara Soranno
- Raffaella Massafra
- Francesco Giotta
- Alfredo Zito
- Erika Francesca Di Benedetto
Institutions
- Istituto Tumori Bari (IT)
Publication Details
- Journal
- PLoS ONE
- Published
- 2024-11-21
- DOI
- https://doi.org/10.1371/journal.pone.0312036
- Citations
- 1
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.35
Funders
- Ministero della Salute