Multimodal Deep Learning for Prognosis Prediction in Renal Cancer.

ABSTRACT:

Background

Clear-cell renal cell carcinoma (ccRCC) is common and associated with substantial mortality. TNM stage and histopathological grading have been the sole determinants of a patient's prognosis for decades and there are few prognostic biomarkers used in clinical routine. Management of ccRCC involves multiple disciplines such as urology, radiology, oncology, and pathology and each of these specialties generates highly complex medical data. Here, artificial intelligence (AI) could prove extremely powerful to extract meaningful information to benefit patients.

Objective

In the study, we developed and evaluated a multimodal deep learning model (MMDLM) for prognosis prediction in ccRCC.

Design setting and participants

Two mixed cohorts of non-metastatic and metastat

SUBMITTER: Schulz S 

PROVIDER: S-EPMC8651560 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature