Autor(es): Sousa, Regina ; Peixoto, Hugo ; Guimarães, Tiago André Saraiva ; Abelha, António ; Machado, José Manuel
Data: 2024
Identificador Persistente: https://hdl.handle.net/1822/89359
Origem: RepositóriUM - Universidade do Minho
Assunto(s): API; Clinical Test Results; Data Warehouse; Health Data Standards; Knowledge Discovery; Real-Time Information Systems
Healthcare facilities use huge quantities of real-time and analytical data to discover meaningful information from patient clinical lab results. Advanced analytics and machine learning algorithms help doctors identify and treat patients more accurately. Accurate models must be trained, tested, and validated with enough data. New real-time data allows healthcare practitioners to quickly and accurately analyse patient demands. Healthcare organizations can improve patient care and outcomes through knowledge discovery. The goal of this effort is to develop a real-time data repository based on patient clinical exams. This collection feeds real-time monitoring panels and machine or deep learning algorithms that forecast patient progression from clinical lab results. Integrate HL7 messages from diverse sources, preprocess them, and add them to an API-accessible data warehouse. In conclusion, the proposed method creates an international-standard data warehouse. This data warehouse can increase healthcare decision-making accuracy and efficacy when utilised with machine learning models, improving patient care and outcomes through more personalised treatment options.
