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Found 4 papers, 1 papers with code
MultiNet with Transformers: A Model for Cancer Diagnosis Using Images
Cancer is a leading cause of death in many countries.
A Deep Learning Study on Osteosarcoma Detection from Histological Images
In this study, transfer learning techniques, pre-trained CNNs, are adapted to a public dataset on osteosarcoma histological images to detect necrotic images from non-necrotic and healthy tissues.
Predicting Urban Dispersal Events: A Two-Stage Framework through Deep Survival Analysis on Mobility Data
We propose a two-stage framework (DILSA), where a deep learning model combined with survival analysis is developed to predict the probability of a dispersal event and its demand volume.
Deep segmentation networks predict survival of non-small cell lung cancer
Here we show that CNN trained to perform the tumor segmentation task, with no other information than physician contours, identify a rich set of survival-related image features with remarkable prognostic value.
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