Abstract: Methods and systems are provided for diagnosing early stages of inflammatory bowel disease (IBD), IBD severity predictions, and the preventions of invasive cancers associated with IBD. Deep learning methods are used for accurate histologic assessment of IBD in one or more target patients. In aspects, IBD associated dysplasia and adenocarcinoma is detected from histopathology data. For example, a deep learning model is modified and trained using a training data set comprising histopathology images to enable Bayesian deep learning. In aspects, the training data set may be labeled based on genetic and immunologic factors. A target patient can be diagnosed as having IBD at a particular severity level based on an output by the deep learned model. Additionally, a care plan for the target patient may be determined, organized, or modified based on the output provided by the deep learned model.