A roadmap for artificial intelligence in pain medicine: current status, opportunities, and requirements DOI
Meredith C B Adams, James Bowness, Ariana M. Nelson

et al.

Current Opinion in Anaesthesiology, Journal Year: 2025, Volume and Issue: unknown

Published: April 24, 2025

Purpose of review Artificial intelligence (AI) represents a transformative opportunity for pain medicine, offering potential solutions to longstanding challenges in assessment and management. This synthesizes the current state AI applications with strategic framework implementation, highlighting established adaptation pathways from adjacent medical fields. Recent findings In acute pain, systems have achieved regulatory approval ultrasound guidance regional anesthesia shown promise automated scoring through facial expression analysis. For chronic management, machine learning algorithms improved diagnostic accuracy musculoskeletal conditions enhanced treatment selection predictive modeling. Successful integration requires interdisciplinary collaboration physician coleadership throughout development process, specific adaptations needed pain-specific challenges. Summary roadmap outlines comprehensive methodological emphasizing four key phases: problem definition, algorithm development, validation, implementation. Critical areas future include perioperative trajectory prediction, real-time procedural guidance, personalized optimization. Success ultimately depends on maintaining strong partnerships between clinicians, developers, researchers while addressing ethical, regulatory, educational considerations.

Language: Английский

Ethical considerations of AI-driven content in anesthesia practice DOI Open Access
Lalit Gupta

Indian Journal of Clinical Anaesthesia, Journal Year: 2025, Volume and Issue: 12(1), P. 1 - 3

Published: Jan. 15, 2025

Language: Английский

Citations

0

Consciousness Research Through Pain DOI Open Access
Dong Ah Shin, Min Cheol Chang

Healthcare, Journal Year: 2025, Volume and Issue: 13(3), P. 332 - 332

Published: Feb. 6, 2025

Background/Objectives: Consciousness is a complex and elusive phenomenon encompassing self-awareness, sensory perception, emotions, cognition. Despite significant advances in neuroscience, understanding the neural mechanisms underlying consciousness remains challenging. Pain, as subjective multifaceted experience, offers unique lens for exploring by integrating inputs with emotional cognitive dimensions. This study examines relationship between pain, highlighting potential of pain model interplay experience activity. Methods: Literature review. Results: Key theories consciousness, such Global Workspace Theory Integrated Information Theory, provide diverse frameworks interpreting emergence consciousness. Similarly, research emphasizes role interpretation context shaping experiences, reflecting broader challenges studies. The limitations current methodologies, particularly difficulty objectively measuring phenomena, like are also addressed. highlights importance correlates, particular focus on brain regions, anterior cingulate cortex insula, which bridge experiences. By analyzing shared attributes this underscores to serve measurable proxy research. Conclusions: Ultimately, it contributes unraveling philosophical underpinnings offering implications mental health treatment advancements artificial intelligence. fills critical gap leveraging reproducible combining theoretical empirical evidence, novel insights into how emerges from processes.

Language: Английский

Citations

0

A roadmap for artificial intelligence in pain medicine: current status, opportunities, and requirements DOI
Meredith C B Adams, James Bowness, Ariana M. Nelson

et al.

Current Opinion in Anaesthesiology, Journal Year: 2025, Volume and Issue: unknown

Published: April 24, 2025

Purpose of review Artificial intelligence (AI) represents a transformative opportunity for pain medicine, offering potential solutions to longstanding challenges in assessment and management. This synthesizes the current state AI applications with strategic framework implementation, highlighting established adaptation pathways from adjacent medical fields. Recent findings In acute pain, systems have achieved regulatory approval ultrasound guidance regional anesthesia shown promise automated scoring through facial expression analysis. For chronic management, machine learning algorithms improved diagnostic accuracy musculoskeletal conditions enhanced treatment selection predictive modeling. Successful integration requires interdisciplinary collaboration physician coleadership throughout development process, specific adaptations needed pain-specific challenges. Summary roadmap outlines comprehensive methodological emphasizing four key phases: problem definition, algorithm development, validation, implementation. Critical areas future include perioperative trajectory prediction, real-time procedural guidance, personalized optimization. Success ultimately depends on maintaining strong partnerships between clinicians, developers, researchers while addressing ethical, regulatory, educational considerations.

Language: Английский

Citations

0