EXPLAINABLE ARTIFICIAL INTELLIGENCE (XAI) TO PREDICT SEPSIS IN ICU USING ELECTRONIC HEALTH RECORDS

Sepsis early identification is pivotal for improving its management outcomes. Machine learning (ML) has the potential to predict sepsis automatically. However, clinicians don’t fully trust prediction results from ML. Explainable Artificial Intelligence (XAI) serves as a bridge to build clinicians’ t...

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Bibliographic Details
Main Author: Ariyo Kresnadhi, Gregorius
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/80978
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Institution: Institut Teknologi Bandung
Language: Indonesia