From Expert Systems to Ambient and Augmented Care: AI in Internal Medicine, Dermatology, Neurology and Neurosurgery
<p>Artificial intelligence (AI) is now woven into the everyday clinical practice of internal medicine, neurology, neurosurgery, and dermatology, transforming how clinicians triage, diagnose, document, and operate. From the early rule-based systems of the 1970s to today’s deep-learning platform...
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| Autores principales: | , , |
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| Formato: | Capítulo de libro |
| Lenguaje: | inglés |
| Publicado: |
IntechOpen
2026
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| Materias: | |
| Acceso en línea: | https://www.intechopen.com/chapters/1237227 |
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| Sumario: | <p>Artificial intelligence (AI) is now woven into the everyday clinical practice of internal medicine, neurology, neurosurgery, and dermatology, transforming how clinicians triage, diagnose, document, and operate. From the early rule-based systems of the 1970s to today’s deep-learning platforms and multimodal foundation models, the evolution of medical AI reflects simultaneous advances in data availability, computational power, and regulatory oversight. Contemporary tools – automated stroke triage, rapid-response EEG, seizure-detection wearables, dermatologic image classifiers, and augmented-reality surgical navigation – have accelerated clinical workflows while raising new questions about validation, safety, and equity. This chapter traces that trajectory and examines the distinction between regulatory clearance, technical accuracy, and true clinical benefit. It outlines evidence standards across specialties, highlights lessons from successful and unsuccessful deployments, and provides a practical governance and education framework for integrating AI responsibly into training programs. As AI moves from proof-of-concept to routine care, medical educators must prepare clinicians to critically appraise model outputs, interpret uncertainty, communicate transparently with patients, and engage in continuous monitoring within their institutions. The goal is not to replace clinical judgment but to strengthen it – ensuring that AI becomes a safe, reliable partner in decision-making across the spectrum of acute care, chronic disease management, and procedural practice.</p> |
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| ISBN: | 978-1-80631-094-4 |
| DOI: | 10.5772/intechopen.1014649 |