javiersgjavi/sepsis-review
Baseline to compare the performance of different models with sepsis data from MIMIC-III database
This project provides a standardized way to evaluate artificial intelligence models for predicting sepsis early in ICU patients. It takes clinical data from electronic health records, processes it to handle missing information, and then runs various machine learning models to identify patients at risk of sepsis. Medical researchers, data scientists in healthcare, and clinicians interested in AI-driven early warning systems would find this useful.
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Use this if you are a medical researcher or data scientist evaluating or developing AI models for early sepsis detection and need a robust benchmark for comparing different approaches.
Not ideal if you need a plug-and-play clinical tool for real-time patient monitoring, as this is a research framework for model comparison and optimization.
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HTML
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BSD-3-Clause
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Last pushed
Apr 25, 2025
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