openmedical/registry
← registry

FedSepsis

imported

devices/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…

Machine-generated from the listed sources and not yet reviewed by a human.

FedSepsis project image
GitHub preview card for anondo1969/FedSepsis. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Devices & Hardware
Subcategory
unknown
License
MIT(osi)
Status
maintained
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
clinical-decision-support-system · clinicalbert · deep-learning · early-sepsis-detection · electronic-health-records · federated-learning · gan · health-informatics
Regulatory
unknown
built by · 1

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.

similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • jkclinical-decision-support-system

    Bridging the gap between theory and bedside practice through open-access, physiologically-weighted, evidence based, decision support tools for anesthesia and intensive care.

  • yourphrelectronic-health-records · health-informatics

    yourphr is an open-source, self-hosted, personal/family electronic medical record manager

  • scanrayelectronic-health-records

    Scanner event monitor for web-based scanning of PDF417 barcodes in healthcare setting

  • Clustered-FL-BrainAGEfederated-learning

    Official implementation of paper "Brain Age Estimation Using Structural MRI: A Clustered Federated Learning Approach"

  • ECG-with-XAIfederated-learning

    Code for CNNs based Explainable arrhythmia detection in federated settings

  • federated_hefederated-learning

    Federated learning with homomorphic encryption enables multiple parties to securely co-train artificial intelligence models in pathology and radiology, reaching state-of-the-art performance with…

sources
  1. api.github.com/repos/anondo1969/FedSepsis
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2025-05-05, 7 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/13.json→ .entries["fedsepsis"]

Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.