Work

Optimised cloud EHR: analysis code, trained models and prototype

Year: 2026

Type: software

Abstract: Python code, trained LSTM forecaster and disease-detection model weights, and web prototype for a forecast-driven cloud EHR framework with PSO resource control and multi-label disease detection, evaluated with Nigerian hospital data. The synthetic workload dataset is at https://doi.org/10.5281/zenodo.23612034. No patient data are included.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.23620606

Author: Adoghe, Olumhense

Institution: Achievers University

Language: English

Topic: Cloud Computing and Resource Management

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W7224813384

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