Articles liés à Artificial Intelligence Applied to Emergency Medicine:...
Artificial Intelligence Applied to Emergency Medicine: Clinical Decision Support, Diagnostic Reasoning, Triage Optimization, Risk Stratification, and Acute Care Innovation - Couverture souple
Livre 2 sur 3: The Elling Emergency Medicine Series
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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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Artificial Intelligence Applied to Emergency Medicine (Paperback)
impression à la demandeVendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
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Paperback. Etat : new. Paperback. 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9798180052148
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Artificial Intelligence Applied to Emergency Medicine: Clinical Decision Support, Diagnostic Reasoning, Triage Optimization, Risk Stratification, and ... (The Elling Emergency Medicine Series)
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Artificial Intelligence Applied to Emergency Medicine
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Artificial Intelligence Applied to Emergency Medicine
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Artificial Intelligence Applied to Emergency Medicine (Paperback)
impression à la demandeVendeur : CitiRetail, Stevenage, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Paperback. Etat : new. Paperback. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798180052148
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Artificial Intelligence Applied to Emergency Medicine : Clinical Decision Support, Diagnostic Reasoning, Triage Optimization, Risk Stratification, and Acute Care Innovation
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. 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
Acheter neuf
EUR 240
Expédition à EUR 63,51
Expédition depuis Allemagne vers Etats-Unis
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