Text-EGM
importedsoftware/text-egm
[CHIL 2024] Interpretation of Intracardiac Electrograms Through Textual Representations
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- CC0-1.0(cc)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- arxiv.org/abs/2402.01115
- Repository
- github.com/willxxy/Text-EGM
- Documentation
- unknown
- Tags
- cardiology · deep-learning · electrophysiology · healthcare · interpretability · language-model · machine-learning · masked-language-models
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- MentalLLaMAinterpretability · language-model
This repository introduces MentaLLaMA, the first open-source instruction following large language model for interpretable mental health analysis.
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BRAVEHEART: Open-source software for automated electrocardiographic and vectorcardiographic analysis
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A system for automating the design of predictive modeling pipelines tailored for clinical prognosis.
- DeepCardiologycardiology · healthcare
Implementations of deep and other ML approaches for cardiology.
- ECG-MIMICcardiology · healthcare
Repository for the paper 'Prospects for AI-Enhanced ECG as a Unified Screening Tool for Cardiac and Non-Cardiac Conditions -- An Explorative Study in Emergency Care'.
- CLATinterpretability
[TMI 2024] Code for "Concept-based Lesion Aware Transformer for Interpretable Retinal Disease Diagnosis"
- api.github.com/repos/willxxy/Text-EGMretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2024-09-04, 12 stars, license reported as CC0-1.0. Category and schematic were assigned by keyword heuristics and are unreviewed.
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/v1/entries/60.json→ .entries["text-egm"]
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