Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
A Transparency System for ICU Using Machine Learning and AI
1
Zitationen
5
Autoren
2024
Jahr
Abstract
Patients in ICUs risk death. Years of opacity, miscommunication, and lack of real-time oversight have compounded medical errors and damaged stakeholder trust in this vital situation. The new ICU transparency system uses AI and deep learning to fix these concerns. Healthcare providers and patients face many unknowns. Medication errors, unmonitored vital signs, and lack of real-time medical data have harmed patient care and confidence. The ICU transparency system handles them well. This novel method offers real-time monitoring, accurate medication recording, and transparency. Guardians and healthcare providers can quickly access patient data for decisions. Vital sign analysis employing AI-driven algorithms detects health issues early. A transparent, collaborative, error-reducing healthcare environment boosts confidence and saves lives. The authors revisit systemic issues and the AI-powered critical care transformation approach in this study.
Ähnliche Arbeiten
"Why Should I Trust You?"
2016 · 14.615 Zit.
Coding Algorithms for Defining Comorbidities in ICD-9-CM and ICD-10 Administrative Data
2005 · 10.529 Zit.
A Comprehensive Survey on Graph Neural Networks
2020 · 8.883 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.451 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.948 Zit.