Benjamin-Lee / Benjamin-Lee/deep-rules

Setting the standards for machine learning in biology

Open
#203 0 comments 0 reactions 0 assignees View on GitHub
paper
Dominant language
HTML
Stars
226
Forks
44
PR merge metrics
No merged PRs in 30d

Description

This commentary covers some pitfalls of deep learning in biology and calls for better benchmarking
> Machine learning is a branch of artificial intelligence (AI) involving computer programs that are able to improve their own performance through experience (training). The diverse applications of new ‘deep learning’ approaches with neural networks are now expanding into the field of biology. But these applications to biological data require more scrutiny and caution to increase the standards of publishing and allow the AI revolution in biology to take off.

https://doi.org/10.1038/s41580-019-0176-5
ReadCube: https://rdcu.be/bR8No

Contributor guide

Open the contributing guide

Research direction

No file, test, or entry point is identified in the issue. Start by reading the linked commentary and determine which manuscript content or benchmarking standards should change; the issue is done only when that scope and the resulting manuscript update are defined.

Written by the indexing model from the issue text.

Assessment

Tech stack
machine-learning
Domain
bioinformatics, content
Issue type
Documentation
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
20/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.