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Intelligent, Autonomous Machines in Surgery.
Loftus, Tyler J; Filiberto, Amanda C; Balch, Jeremy; Ayzengart, Alexander L; Tighe, Patrick J; Rashidi, Parisa; Bihorac, Azra; Upchurch, Gilbert R.
Afiliação
  • Loftus TJ; Department of Surge ry, University of Florida Health, Gainesville, Florida.
  • Filiberto AC; Department of Surge ry, University of Florida Health, Gainesville, Florida.
  • Balch J; Department of Surge ry, University of Florida Health, Gainesville, Florida.
  • Ayzengart AL; Department of Surge ry, University of Florida Health, Gainesville, Florida.
  • Tighe PJ; Departments of Biomedical Engineering, Computer and Information Science and Engineering, and Electrical and Computer Engineering, University of Florida, Gainesville, Florida.
  • Rashidi P; Departments of Anesthesiology, Orthopedics, and Information Systems/Operations Management, University of Florida Health, Gainesville, Florida.
  • Bihorac A; Department of Medicine, University of Florida Health, Gainesville, Florida.
  • Upchurch GR; Department of Surge ry, University of Florida Health, Gainesville, Florida. Electronic address: gib.upchurch@surgery.ufl.edu.
J Surg Res ; 253: 92-99, 2020 09.
Article em En | MEDLINE | ID: mdl-32339787
ABSTRACT
Surgeons perform two primary tasks operating and engaging patients and caregivers in shared decision-making. Human dexterity and decision-making are biologically limited. Intelligent, autonomous machines have the potential to augment or replace surgeons. Rather than regarding this possibility with denial, ire, or indifference, surgeons should understand and steer these technologies. Closer examination of surgical innovations and lessons learned from the automotive industry can inform this process. Innovations in minimally invasive surgery and surgical decision-making follow classic S-shaped curves with three phases (1) introduction of a new technology, (2) achievement of a performance advantage relative to existing standards, and (3) arrival at a performance plateau, followed by replacement with an innovation featuring greater machine autonomy and less human influence. There is currently no level I evidence demonstrating improved patient outcomes using intelligent, autonomous machines for performing operations or surgical decision-making tasks. History suggests that if such evidence emerges and if the machines are cost effective, then they will augment or replace humans, initially for simple, common, rote tasks under close human supervision and later for complex tasks with minimal human supervision. This process poses ethical challenges in assigning liability for errors, matching decisions to patient values, and displacing human workers, but may allow surgeons to spend less time gathering and analyzing data and more time interacting with patients and tending to urgent, critical-and potentially more valuable-aspects of patient care. Surgeons should steer these technologies toward optimal patient care and net social benefit using the uniquely human traits of creativity, altruism, and moral deliberation.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Sistemas de Apoio a Decisões Clínicas / Invenções / Procedimentos Cirúrgicos Robóticos / Cirurgiões Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Sistemas de Apoio a Decisões Clínicas / Invenções / Procedimentos Cirúrgicos Robóticos / Cirurgiões Idioma: En Ano de publicação: 2020 Tipo de documento: Article