11 wiki results in DeepPhe/models
Competency Questions Validation of the DeepPhe models requires consideration of the types of questions that they might (and might not) be able to answer. Although such efforts are almost by definition ...
Initial DeepPhe Contextual Inquiry Protocol During the interview, we will ask the informant to conduct relevant tasks, explaining what is being done, why it must be done, and how it is done. As the informant ...
The project described is supported by Grant Number 1U24CA184407-01 from the National Cancer Institute at the US National Institutes of Health. This work is part of the NCI's Informatics Technology ...
Introduction This repository contains information models as developed for the Cancer Deep Phenotyping project (DeepPhe, R. Jacobson & G. Savova, PIs). Materials in this wiki providing support material ...
Information modeling interview protocol As we develop draft and final models, we will be validating them with the domain scientists who are collaborators on our grant. The purpose of this validation is ...
Goals Encourage the broad use of DeepPhe tools and models, while maintaining openness and attribution. Comply with resource sharing plan as submitted to NIH. See, for example ITCR policies Distinction ...
The following are publications and presentations crediting the Cancer Deep Phenotype Extraction (DeepPhe) project: Hochheiser H; Jacobson R; Washington N; Denny J; Savova G. 2015. Natural language processing ...
User personae : describing potential users of DeepPhe information models. Contextual interview protocol : used to interview informants regarding research workflows. Information modeling interview protocol ...
Introduction Presented here is a series of stakeholder or user descriptions - referred to here as personae , which informed preliminary development of the cancer models. Translational Scientist with “Dry ...
Welcome to the Cancer Deep Phenotype Extraction (DeepPhe) project. Cancer is a genomic disease, with enormous heterogeneity in its behavior. In the past, our methods for categorization, prediction of outcome, ...