Artificial Intelligence Applied to Emergency Medicine : Clinical Decision Support, Diagnostic Reasoning, Triage Optimization, Risk Stratification, and Acute Care Innovation

Robert Elling

ISBN 13: 9798180052148

Edité par Independently Published Jun 2026, 2026

A propos de cet article

Neuware - Emergency medicine demands clear judgment, rapid prioritization, and reliable decisions under pressure. As artificial intelligence becomes increasingly integrated into acute care, clinicians and healthcare leaders need a practical framework for using these tools safely, thoughtfully, and effectively at the bedside.Artificial Intelligence Applied to Emergency Medicine provides a clinically rigorous guide to understanding how AI can support triage, diagnostic reasoning, risk stratification, treatment decisions, documentation, patient flow, and emergency department operations. Written with a strong focus on safety, validation, bias, local protocols, and human oversight, the book shows how AI can strengthen clinical practice while preserving clinician accountability and patient-centered judgment.Readers move from foundational AI concepts to real-world emergency medicine applications, learning how to interpret model outputs, evaluate clinical tools, recognize failure modes, integrate decision support into workflow, and maintain safe boundaries in high-risk acute care environments. The result is a practical and measured understanding of how AI can become a dependable clinical support layer across the emergency care pathway.Inside, you'll learn how to: - Apply AI-supported clinical reasoning across triage, diagnosis, imaging, laboratory interpretation, medication safety, treatment planning, and disposition decisions.- Evaluate AI tools before implementation by assessing evidence, local validation, workflow fit, bias, privacy, governance, and patient-safety risk.- Use generative AI responsibly for clinical documentation, discharge instructions, handoffs, consultations, and transfer summaries.- Recognize red flags and failure modes while maintaining human oversight, clear documentation, and clinician-led decision-making.Designed for emergency physicians, residents, advanced practice clinicians, nurses, informatics professionals, department leaders, and healthcare administrators, this book offers a practical reference for navigating AI-supported acute care with confidence, discipline, and clinical responsibility.Build a safer, more informed, and more effective approach to artificial intelligence in emergency medicine-while keeping patient context and clinical judgment at the center of every decision.

N° de réf. du vendeur 9798180052148

Détails bibliographiques

• Titre: Artificial Intelligence Applied to Emergency Medicine : Clinical Decision Support, Diagnostic Reasoning, Triage Optimization, Risk Stratification, and Acute Care Innovation
• Éditeur: Independently Published Jun 2026
• Date de parution: 2026
• Langue: anglais
• ISBN à 13 chiffres: 9798180052148
• Reliure: Taschenbuch
• État de l'article: Neu
• Dimensions: 279 L x 216 H x 16 P (en millimètres) 279 millimètres de largeur par 216 millimètres de hauteur par 16 millimètres de profondeur
• Poids: 701 grammes

A propos de ce titre

Synopsis

Emergency medicine demands clear judgment, rapid prioritization, and reliable decisions under pressure. As artificial intelligence becomes increasingly integrated into acute care, clinicians and healthcare leaders need a practical framework for using these tools safely, thoughtfully, and effectively at the bedside.

Artificial Intelligence Applied to Emergency Medicine provides a clinically rigorous guide to understanding how AI can support triage, diagnostic reasoning, risk stratification, treatment decisions, documentation, patient flow, and emergency department operations. Written with a strong focus on safety, validation, bias, local protocols, and human oversight, the book shows how AI can strengthen clinical practice while preserving clinician accountability and patient-centered judgment.

Readers move from foundational AI concepts to real-world emergency medicine applications, learning how to interpret model outputs, evaluate clinical tools, recognize failure modes, integrate decision support into workflow, and maintain safe boundaries in high-risk acute care environments. The result is a practical and measured understanding of how AI can become a dependable clinical support layer across the emergency care pathway.

Inside, you’ll learn how to:

• Apply AI-supported clinical reasoning across triage, diagnosis, imaging, laboratory interpretation, medication safety, treatment planning, and disposition decisions.

• Evaluate AI tools before implementation by assessing evidence, local validation, workflow fit, bias, privacy, governance, and patient-safety risk.

• Use generative AI responsibly for clinical documentation, discharge instructions, handoffs, consultations, and transfer summaries.

• Recognize red flags and failure modes while maintaining human oversight, clear documentation, and clinician-led decision-making.

Designed for emergency physicians, residents, advanced practice clinicians, nurses, informatics professionals, department leaders, and healthcare administrators, this book offers a practical reference for navigating AI-supported acute care with confidence, discipline, and clinical responsibility.

Build a safer, more informed, and more effective approach to artificial intelligence in emergency medicine—while keeping patient context and clinical judgment at the center of every decision.