Intelligent, Autonomous Machines in Surgery

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...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:The Journal of surgical research 2020-09, Vol.253, p.92-99
Hauptverfasser: Loftus, Tyler J., Filiberto, Amanda C., Balch, Jeremy, Ayzengart, Alexander L., Tighe, Patrick J., Rashidi, Parisa, Bihorac, Azra, Upchurch, Gilbert R.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 99
container_issue
container_start_page 92
container_title The Journal of surgical research
container_volume 253
creator Loftus, Tyler J.
Filiberto, Amanda C.
Balch, Jeremy
Ayzengart, Alexander L.
Tighe, Patrick J.
Rashidi, Parisa
Bihorac, Azra
Upchurch, Gilbert R.
description 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.
doi_str_mv 10.1016/j.jss.2020.03.046
format Article
fullrecord <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7594619</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0022480420301785</els_id><sourcerecordid>2395626684</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3666-44f4cb35e6529948d64b95f2d874c30ecb2cab553974c22a8c6bd2bc6a8ee3db3</originalsourceid><addsrcrecordid>eNp9kE1LAzEQhoMotlZ_gBfpUdBds0k2u0EQSvGjUPGgnkM2O9tm2Y-a7Bb6701pLXrxNAzzzjvvPAhdRjiMcMTvyrB0LiSY4BDTEDN-hIYRFnGQ8oQeoyHGhAQsxWyAzpwrse9FQk_RgBJKRZImQ3QzazqoKrOAprsdT_qubdq67d34VemlacCNTTN-7-0C7OYcnRSqcnCxryP0-fT4MX0J5m_Ps-lkHmjKOQ8YK5jOaAw8JkKwNOcsE3FB8jRhmmLQGdEqi2OfgGlCVKp5lpNMc5UC0DyjI_Sw8131WQ259tGsquTKmlrZjWyVkX8njVnKRbuWSSwYj4Q3uN4b2ParB9fJ2jjt31QN-N8koSLmhPOUeWm0k2rbOmehOJyJsNxClqX0kOUWssRUesh-5-p3vsPGD1UvuN8JwFNaG7DSaQONhtxY0J3MW_OP_TcC7o2Z</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2395626684</pqid></control><display><type>article</type><title>Intelligent, Autonomous Machines in Surgery</title><source>Elsevier ScienceDirect Journals</source><creator>Loftus, Tyler J. ; Filiberto, Amanda C. ; Balch, Jeremy ; Ayzengart, Alexander L. ; Tighe, Patrick J. ; Rashidi, Parisa ; Bihorac, Azra ; Upchurch, Gilbert R.</creator><creatorcontrib>Loftus, Tyler J. ; Filiberto, Amanda C. ; Balch, Jeremy ; Ayzengart, Alexander L. ; Tighe, Patrick J. ; Rashidi, Parisa ; Bihorac, Azra ; Upchurch, Gilbert R.</creatorcontrib><description>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.</description><identifier>ISSN: 0022-4804</identifier><identifier>EISSN: 1095-8673</identifier><identifier>DOI: 10.1016/j.jss.2020.03.046</identifier><identifier>PMID: 32339787</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Artificial intelligence ; Automation ; Innovation ; Machine learning ; Surgery</subject><ispartof>The Journal of surgical research, 2020-09, Vol.253, p.92-99</ispartof><rights>2020 Elsevier Inc.</rights><rights>Copyright © 2020 Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3666-44f4cb35e6529948d64b95f2d874c30ecb2cab553974c22a8c6bd2bc6a8ee3db3</citedby><cites>FETCH-LOGICAL-c3666-44f4cb35e6529948d64b95f2d874c30ecb2cab553974c22a8c6bd2bc6a8ee3db3</cites><orcidid>0000-0002-1826-7884 ; 0000-0002-5745-2863</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0022480420301785$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,776,780,881,3536,27903,27904,65309</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32339787$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Loftus, Tyler J.</creatorcontrib><creatorcontrib>Filiberto, Amanda C.</creatorcontrib><creatorcontrib>Balch, Jeremy</creatorcontrib><creatorcontrib>Ayzengart, Alexander L.</creatorcontrib><creatorcontrib>Tighe, Patrick J.</creatorcontrib><creatorcontrib>Rashidi, Parisa</creatorcontrib><creatorcontrib>Bihorac, Azra</creatorcontrib><creatorcontrib>Upchurch, Gilbert R.</creatorcontrib><title>Intelligent, Autonomous Machines in Surgery</title><title>The Journal of surgical research</title><addtitle>J Surg Res</addtitle><description>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.</description><subject>Artificial intelligence</subject><subject>Automation</subject><subject>Innovation</subject><subject>Machine learning</subject><subject>Surgery</subject><issn>0022-4804</issn><issn>1095-8673</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kE1LAzEQhoMotlZ_gBfpUdBds0k2u0EQSvGjUPGgnkM2O9tm2Y-a7Bb6701pLXrxNAzzzjvvPAhdRjiMcMTvyrB0LiSY4BDTEDN-hIYRFnGQ8oQeoyHGhAQsxWyAzpwrse9FQk_RgBJKRZImQ3QzazqoKrOAprsdT_qubdq67d34VemlacCNTTN-7-0C7OYcnRSqcnCxryP0-fT4MX0J5m_Ps-lkHmjKOQ8YK5jOaAw8JkKwNOcsE3FB8jRhmmLQGdEqi2OfgGlCVKp5lpNMc5UC0DyjI_Sw8131WQ259tGsquTKmlrZjWyVkX8njVnKRbuWSSwYj4Q3uN4b2ParB9fJ2jjt31QN-N8koSLmhPOUeWm0k2rbOmehOJyJsNxClqX0kOUWssRUesh-5-p3vsPGD1UvuN8JwFNaG7DSaQONhtxY0J3MW_OP_TcC7o2Z</recordid><startdate>20200901</startdate><enddate>20200901</enddate><creator>Loftus, Tyler J.</creator><creator>Filiberto, Amanda C.</creator><creator>Balch, Jeremy</creator><creator>Ayzengart, Alexander L.</creator><creator>Tighe, Patrick J.</creator><creator>Rashidi, Parisa</creator><creator>Bihorac, Azra</creator><creator>Upchurch, Gilbert R.</creator><general>Elsevier Inc</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-1826-7884</orcidid><orcidid>https://orcid.org/0000-0002-5745-2863</orcidid></search><sort><creationdate>20200901</creationdate><title>Intelligent, Autonomous Machines in Surgery</title><author>Loftus, Tyler J. ; Filiberto, Amanda C. ; Balch, Jeremy ; Ayzengart, Alexander L. ; Tighe, Patrick J. ; Rashidi, Parisa ; Bihorac, Azra ; Upchurch, Gilbert R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3666-44f4cb35e6529948d64b95f2d874c30ecb2cab553974c22a8c6bd2bc6a8ee3db3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Artificial intelligence</topic><topic>Automation</topic><topic>Innovation</topic><topic>Machine learning</topic><topic>Surgery</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Loftus, Tyler J.</creatorcontrib><creatorcontrib>Filiberto, Amanda C.</creatorcontrib><creatorcontrib>Balch, Jeremy</creatorcontrib><creatorcontrib>Ayzengart, Alexander L.</creatorcontrib><creatorcontrib>Tighe, Patrick J.</creatorcontrib><creatorcontrib>Rashidi, Parisa</creatorcontrib><creatorcontrib>Bihorac, Azra</creatorcontrib><creatorcontrib>Upchurch, Gilbert R.</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>The Journal of surgical research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Loftus, Tyler J.</au><au>Filiberto, Amanda C.</au><au>Balch, Jeremy</au><au>Ayzengart, Alexander L.</au><au>Tighe, Patrick J.</au><au>Rashidi, Parisa</au><au>Bihorac, Azra</au><au>Upchurch, Gilbert R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Intelligent, Autonomous Machines in Surgery</atitle><jtitle>The Journal of surgical research</jtitle><addtitle>J Surg Res</addtitle><date>2020-09-01</date><risdate>2020</risdate><volume>253</volume><spage>92</spage><epage>99</epage><pages>92-99</pages><issn>0022-4804</issn><eissn>1095-8673</eissn><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.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>32339787</pmid><doi>10.1016/j.jss.2020.03.046</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-1826-7884</orcidid><orcidid>https://orcid.org/0000-0002-5745-2863</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0022-4804
ispartof The Journal of surgical research, 2020-09, Vol.253, p.92-99
issn 0022-4804
1095-8673
language eng
recordid cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7594619
source Elsevier ScienceDirect Journals
subjects Artificial intelligence
Automation
Innovation
Machine learning
Surgery
title Intelligent, Autonomous Machines in Surgery
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-23T16%3A48%3A35IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Intelligent,%20Autonomous%20Machines%20in%20Surgery&rft.jtitle=The%20Journal%20of%20surgical%20research&rft.au=Loftus,%20Tyler%20J.&rft.date=2020-09-01&rft.volume=253&rft.spage=92&rft.epage=99&rft.pages=92-99&rft.issn=0022-4804&rft.eissn=1095-8673&rft_id=info:doi/10.1016/j.jss.2020.03.046&rft_dat=%3Cproquest_pubme%3E2395626684%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2395626684&rft_id=info:pmid/32339787&rft_els_id=S0022480420301785&rfr_iscdi=true