@agitter is no longer updating the outline, we are no longer accepting new sections

Of course you should feel welcome to contribute to sections that already exist. We're also looking for people to take primary responsibility for sections. I'll copy an e-mail from @agitter below that has our - as far as I know - most up to date status:

As described in the intro https://github.com/greenelab/deep-review/blob/master/sections/02_intro.md we’ve broken the paper into Categorize, Study, and Treat sections. Each of these has been outlined, though we welcome suggestions for new sub-sections. There is also a Discussion of general issues pertinent to all three application areas and future outlook. Here are that primary topics in each section that are unclaimed as far as I know.

Categorize:

• Finished a first draft of everything

Study:

• Finished a first draft of everything

Treat:

• Finished a first draft of everything

Discussion:

• Finished a first draft of everything (pending pull requests in progress)

#88 and #2 provide some context on our goals for the review and how we hope to differentiate it from existing papers. We don’t want to enumerate all deep learning papers in biomedicine so some of the Study sub-sections may be cut entirely if there is nothing especially interesting to say about them. To start working on a sub-section, you can create a pull request. #147 is an example of a completed pull request and #174 is one I’m actively working on where I’m still outlining and searching for relevant literature.

Please let us know if you want to discuss anything else specific or else we can take the discussion to GitHub so that others can contribute.

Edit by @agitter
@cgreene had good suggestions in #200 that are helpful prompts for anyone starting a topic sub-section

• introductory paragraph to the problem and/or data type
• places where deep NNs have been successful [with some interpretation as to why]
• places where deep NNs have not been successful [again maybe with some why]
• places where deep NNs have not been applied, but you think they should be