newsletter and doc updates for memory optimizations #745
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
This pull request announces a major memory optimization for PyHealth, enabling it to process large EHR datasets like MIMIC-IV on machines with only 16GB of RAM. The update is highlighted in the December 2025 newsletter and reflected in the version bump to
2.0a13. The most important changes are summarized below:Newsletter and Documentation Updates:
2025-12-memory-optimizationto the newsletter archive, detailing the backend overhaul and its impact on memory usage for large-scale clinical data processing.docs/newsletter/2025-12-memory-optimization.rstwith an in-depth explanation of the memory optimization, including benchmarks, technical changes, and a call for community feedback.Release Version Update:
pyproject.tomlfrom2.0a12to2.0a13to reflect the release of the new memory optimization feature.