An artificial intelligence-based model exploiting H&E images to predict recurrence in negative sentinel lymph-node melanoma patients.
Maria Colomba ComesLivia FucciSabino StrippoliSamantha BoveGerardo CazzatoCarmen ColangiuliIvana De RisiIleana De RomaAnnarita FanizziFabio MeleMaurizio RessaConcetta SaponaroClara SorannoRosita TinelliMichele GuidaAlfredo ZitoRaffaella MassafraPublished in: Journal of translational medicine (2024)
Our approach represents a first effort to develop a non-invasive prognostic method to better define the recurrence risk and improve the management of SLN- melanoma patients.
Keyphrases
- artificial intelligence
- end stage renal disease
- sentinel lymph node
- newly diagnosed
- chronic kidney disease
- machine learning
- deep learning
- prognostic factors
- peritoneal dialysis
- early stage
- neoadjuvant chemotherapy
- big data
- radiation therapy
- convolutional neural network
- free survival
- rectal cancer
- skin cancer
- locally advanced