https://ramosrenzo.github.io/COVID-LLM/
Assessing LLMs—AAM, DNABERT, DNABERT-2, GROVER—to improve the prediction of COVID-19 status ("Positive" or "Not detected") using microbiome data
https://ramosrenzo.github.io/COVID-LLM/
aam covid-19 dnabert dnabert-2 grover llms
Last synced: 7 months ago
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Assessing LLMs—AAM, DNABERT, DNABERT-2, GROVER—to improve the prediction of COVID-19 status ("Positive" or "Not detected") using microbiome data
- Host: GitHub
- URL: https://ramosrenzo.github.io/COVID-LLM/
- Owner: ramosrenzo
- Created: 2025-01-09T00:39:14.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-27T04:10:29.000Z (about 1 year ago)
- Last Synced: 2025-04-27T05:19:18.090Z (about 1 year ago)
- Topics: aam, covid-19, dnabert, dnabert-2, grover, llms
- Language: Python
- Homepage: https://ramosrenzo.github.io/COVID-LLM/
- Size: 4.02 GB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- Awesome-Specialized-Medical-LLMs - Assessing LLMs to Improve the Prediction of COVID-19 Status Using Microbiome Data - based LLMs (AAM, DNABERT, DNABERT-2, GROVER) for COVID-19 prediction from hospital-derived 16S rRNA microbiome data, demonstrating that domain-specific pretraining (AAM) yields superior predictive performance over general genomic models. | [COVID-LLM](https://github.com/ramosrenzo/COVID-LLM) | (Diseases of the Respiratory System (X))