Deep Learning based detection of tumor tissue compartments improves prognostic immunoprofiling in muscle-invasive bladder cancer
Posted 11th November 2019 by Liv Sewell
Worldwide, bladder cancer (BC) is the 11th most commonly diagnosed cancer. In men, BC is the 7thmost commonly diagnosed cancer worldwide.Although men are more likely to develop BC than women, women present with more advanced disease and have worse survival rates.
Muscle-invasive bladder cancers (MIBC) are cancers that have grown into or through the muscle layers of the bladder wall.
Dr. Katharina Nekolla and Ansh Kapil and their team applied Deep Learning enabled pathology to better understand prognostic factors in MIBC. Here we review the significance of the research and share their original poster.