anondo1969/FedSepsis
Repository for the journal article, 'FedSepsis: A Federated Multi-Modal Deep Learning-Based Internet of Medical Things Application for Early Detection of Sepsis from Electronic Health Records Using Raspberry Pi and Jetson Nano Devices', Mahbub Ul Alam, Rahim Rahmani. Sensors 23, no. 2: 970, https://doi.org/10.3390/s23020970.
This project helps medical professionals detect sepsis early by analyzing electronic health records (EHRs). It takes patient data from various medical devices and servers, even those with limited capacity, and outputs a timely prediction of sepsis onset. This system is designed for clinicians, nurses, and healthcare administrators who need secure and rapid sepsis detection.
No commits in the last 6 months.
Use this if you need a secure, privacy-preserving system to analyze diverse electronic health records for early sepsis detection across different medical facilities using low-cost devices.
Not ideal if you are looking for a standalone diagnostic tool without integrating into an Internet of Medical Things (IoMT) setup or require only single-modality data analysis.
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MIT
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Last pushed
May 05, 2025
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