Weakly-supervised learning for image-based classification of primary melanomas into genomic immune subgroups. (arXiv:2202.11524v1 [eess.IV])

Determining early-stage prognostic markers and stratifying patients for
effective treatment are two key challenges for improving outcomes for melanoma
patients. Previous studies have used tumour transcriptome data to stratify
patients into immune subgroups, which were associated with differential
melanoma specific survival and potential treatment strategies. However,
acquiring transcriptome data is a time-consuming and costly process. Moreover,
it is not routinely used in the current clinical workflow. Here we attempt to
overcome this by developing deep learning models to classify gigapixel …

arxiv classification image learning subgroups supervised learning