Document the Alex |Andre |Gilberto |Shize algorithm

[reubano]

Overview

Participants in the Data Science Bowl produced several algorithms that we would like to incorporate. To help facilitate this effort, we also want to add documentation so that contributors can make an educated decision when selecting an algorithm to incorporate.

Expected Behavior

This documentation should enable people to:

• view the library dependencies and license
• understand its pros/cons
• evaluate its performance/accuracy
• identify which areas of the codebase to target for improvement

Design doc reference: Detect and select

Algorithm info

key	value
team	Alex |Andre |Gilberto |Shize
rank	8
repo	https://github.com/astoc/kaggle_dsb2017
trained models	https://github.com/astoc/kaggle_dsb2017/tree/master/code/Andre/nodule_identifiers
converted branch
ML engine	Keras
engine-version	1.2.2
ML backend	Theano
backend-version
training method
architecture
algorithm
OS
OS version
Python version
CUDA version
cuDNN version
notes

Technical details

• This feature should be implemented as a new markdown file in the docs folder

Acceptance criteria

• [ ] effective documentation for the above

NOTE: All PRs must follow the standard PR checklist.

[tjvananne]

I'm reading through this one right now. Please correct me if I'm wrong, but it seems like the competition target variable was to predict the probability of the patient having cancer as a whole as opposed to the probability of each individual nodule being cancerous?

It looks like most of these go through the same z-slice normalization, lung segmentation, and nodule detection/isolation steps. But then it's the final feature generation steps that might need to be refactored quite a bit to tackle the new problem statement of predicting the probability of each nodule being cancerous. Is that a fair statement?

A feature such as total_number_of_nodules (I made that up as an example) aggregated at the patient level might still be important at the nodule level, but it does seem to imply that the goal was slightly different.

[reubano]

Answer posted here.

[lamby]

@tjvananne Did @reubano's link answer your question? :)

[WGierke]

@lamby same here - is something preventing this issue from getting closed? :)