Current and future applications of artificial intelligence in surgery: implications for clinical practice and research
Surgeons are skilled at making complex decisions over invasive procedures that can save lives and alleviate pain and avoid complications in patients. The knowledge to make these decisions is accumulated over years of schooling and practice. Their experience is in turn shared with others, also via pe...
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| Published in | Frontiers in surgery Vol. 11; p. 1393898 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Switzerland
Frontiers Media S.A
09.05.2024
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| Subjects | |
| Online Access | Get full text |
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| Abstract | Surgeons are skilled at making complex decisions over invasive procedures that can save lives and alleviate pain and avoid complications in patients. The knowledge to make these decisions is accumulated over years of schooling and practice. Their experience is in turn shared with others, also via peer-reviewed articles, which get published in larger and larger amounts every year. In this work, we review the literature related to the use of Artificial Intelligence (AI) in surgery. We focus on what is currently available and what is likely to come in the near future in both clinical care and research. We show that AI has the potential to be a key tool to elevate the effectiveness of training and decision-making in surgery and the discovery of relevant and valid scientific knowledge in the surgical domain. We also address concerns about AI technology, including the inability for users to interpret algorithms as well as incorrect predictions. A better understanding of AI will allow surgeons to use new tools wisely for the benefit of their patients. |
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| AbstractList | Surgeons are skilled at making complex decisions over invasive procedures that can save lives and alleviate pain and avoid complications in patients. The knowledge to make these decisions is accumulated over years of schooling and practice. Their experience is in turn shared with others, also via peer-reviewed articles, which get published in larger and larger amounts every year. In this work, we review the literature related to the use of Artificial Intelligence (AI) in surgery. We focus on what is currently available and what is likely to come in the near future in both clinical care and research. We show that AI has the potential to be a key tool to elevate the effectiveness of training and decision-making in surgery and the discovery of relevant and valid scientific knowledge in the surgical domain. We also address concerns about AI technology, including the inability for users to interpret algorithms as well as incorrect predictions. A better understanding of AI will allow surgeons to use new tools wisely for the benefit of their patients.Surgeons are skilled at making complex decisions over invasive procedures that can save lives and alleviate pain and avoid complications in patients. The knowledge to make these decisions is accumulated over years of schooling and practice. Their experience is in turn shared with others, also via peer-reviewed articles, which get published in larger and larger amounts every year. In this work, we review the literature related to the use of Artificial Intelligence (AI) in surgery. We focus on what is currently available and what is likely to come in the near future in both clinical care and research. We show that AI has the potential to be a key tool to elevate the effectiveness of training and decision-making in surgery and the discovery of relevant and valid scientific knowledge in the surgical domain. We also address concerns about AI technology, including the inability for users to interpret algorithms as well as incorrect predictions. A better understanding of AI will allow surgeons to use new tools wisely for the benefit of their patients. Surgeons are skilled at making complex decisions over invasive procedures that can save lives and alleviate pain and avoid complications in patients. The knowledge to make these decisions is accumulated over years of schooling and practice. Their experience is in turn shared with others, also via peer-reviewed articles, which get published in larger and larger amounts every year. In this work, we review the literature related to the use of Artificial Intelligence (AI) in surgery. We focus on what is currently available and what is likely to come in the near future in both clinical care and research. We show that AI has the potential to be a key tool to elevate the effectiveness of training and decision-making in surgery and the discovery of relevant and valid scientific knowledge in the surgical domain. We also address concerns about AI technology, including the inability for users to interpret algorithms as well as incorrect predictions. A better understanding of AI will allow surgeons to use new tools wisely for the benefit of their patients. |
| Author | Fiocco, Davide Orgill, Dennis P. Morris, Miranda X. Caneva, Tommaso Yiapanis, Paris |
| AuthorAffiliation | 2 Department of Artificial Intelligence, Frontiers Media SA , Lausanne , Switzerland 3 Harvard Medical School, Brigham and Women’s Hospital , Boston, MA , United States 1 Duke University School of Medicine, Duke University Hospital , Durham, NC , United States |
| AuthorAffiliation_xml | – name: 3 Harvard Medical School, Brigham and Women’s Hospital , Boston, MA , United States – name: 2 Department of Artificial Intelligence, Frontiers Media SA , Lausanne , Switzerland – name: 1 Duke University School of Medicine, Duke University Hospital , Durham, NC , United States |
| Author_xml | – sequence: 1 givenname: Miranda X. surname: Morris fullname: Morris, Miranda X. – sequence: 2 givenname: Davide surname: Fiocco fullname: Fiocco, Davide – sequence: 3 givenname: Tommaso surname: Caneva fullname: Caneva, Tommaso – sequence: 4 givenname: Paris surname: Yiapanis fullname: Yiapanis, Paris – sequence: 5 givenname: Dennis P. surname: Orgill fullname: Orgill, Dennis P. |
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| Cites_doi | 10.1097/XCS.0000000000000242 10.1186/s12909-019-1891-5 10.54394/FHEM8239 10.1016/j.eswa.2018.03.058 10.1515/dx-2023-0090 10.1186/s13017-022-00467-3 10.20517/ais.2022.12 10.1097/SLA.0000000000004425 10.1097/SLA.0000000000003460 10.15694/mep.2020.000049.1 10.1097/MOU.0000000000000890 10.1371/journal.pone.0267936 10.1016/j.joi.2019.101004 10.3390/bs12090343 10.3390/ijerph15122796 10.1177/00031348221117042 10.2196/46428 10.1097/GOX.0000000000005290 10.1093/bjsopen/zrac149 10.1016/j.ijsu.2020.05.015 10.1097/SLA.0000000000003931 10.1097/SLA.0000000000003043 10.1177/2192568220915718 10.3934/Neuroscience.2021025 10.1089/end.2020.0137 10.1016/j.wneu.2020.03.029 10.7759/cureus.23662 10.1177/00031348221101503 10.1021/acsenergylett.2c02828 10.1097/SLA.0000000000004736 10.1007/s11548-021-02473-3 10.1007/s00464-021-08999-6 10.1007/978-3-030-64511-3_2 10.3389/fcvm.2022.941148 10.1109/ACCESS.2018.2890388 10.3390/cancers14153803 10.1159/000536393 10.1590/0102-672020220002e1712 10.1097/AS9.0000000000000091 10.1186/s13017-021-00394-9 10.1001/jamasurg.2019.1510 10.13172/2050-2303-2-3-498 10.1109/TMI.2016.2593957 10.1007/s00268-022-06728-1 10.3340/jkns.2022.0130 10.1007/s11948-022-00391-4 10.1007/s11192-022-04504-5 10.1016/j.patter.2023.100796 10.1002/leap.1570 10.1186/s13018-020-02002-z 10.24318/9kvAgrnJ 10.1097/SLA.0000000000002693 10.3340/jkns.2021.0213 10.2196/13930 10.1007/s11701-024-01867-0 10.25259/SNI_877_2022 10.1016/j.jpedsurg.2007.10.012 10.1177/00031348221101490 10.1097/SLA.0000000000002956 10.1016/j.jamcollsurg.2021.02.009 10.1016/j.ymeth.2020.01.011 10.14245/ns.1938404.202 10.3389/frai.2022.955314 10.1038/s41598-024-55568-7 10.1002/jso.26496 10.3390/bioengineering10040465 10.2214/AJR.22.27487 10.1007/s40593-022-00293-3 10.58425/ajt.v2i1.142 10.3389/fmedt.2022.1076755 |
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| Keywords | deep learning—artificial intelligence data science machine learning artificial intelligence surgery |
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| License | 2024 Morris, Fiocco, Caneva, Yiapanis and Orgill. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
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| References | Garrow (B42) 2021; 273 Mofatteh (B50) 2021 Chan (B6) 2019; 5 Feuerriegel (B4) Ulloa (B11) 2023 Dadkhah (B29) 2023; 10 Mari (B7) 2022; 2 Perez-Breva (B54) 2019 Mascagni (B43) 2021; 274 Bravo (B10) 2022 Oleck (B21) 2023; 11 Twinanda (B46) 2017; 36 Hashimoto (B47) 2019; 270 Hu (B35) 2020; 14 Quero (B48) 2022 Bektaş (B12) 2022 Otterbacher (B79) 2023; 4 Zhang (B45) 2021; 16 Knudsen (B3) 2024; 18 Hanson (B23) Soulière (B36) 2021 Axenie (B61) 2020 Guan (B71) 2022 Mirończuk (B24) 2018; 106 Zhang (B75) 2022 Gero (B63) 2022 Stai (B74) 2020 Stribling (B5) 2024; 14 Goh (B9) 2020 Pretzsch (B65) 2022 Ward (B17) 2021 Devlin (B30) Rasouli (B55) 2021 Amedior (B69) 2023 Reimers (B26) Viceconti (B32) 2021; 185 Huriye (B72) 2023 Cobianchi (B66) 2023; 18 Lammers (B39) 2021; 2 Cardenuto (B27) 2022; 28 Loftus (B59) 2019 Sabel (B80) Joulin (B25) Moglia (B20) 2022 Hashimoto (B70) 2018 Cobianchi (B67) 2022 Grimaldi (B37) 2023; 8 Liu (B38) 2022; 219 Morris (B40); 89 Iqbal (B52) 2022 Cacciamani (B14) 2021 Weidener (B19) 2023 Park (B8) 2022; 4 Palmisciano (B49) 2020 Gmyrek (B76) 2023 Singh (B16) 2023 El Hechi (B78) 2021; 232 Abdul Razak (B57) 2023; 5 Agadi (B51) 2023 Chen (B62) 2022 Li (B41) 2021 Kousha (B22) 2024; 37 Weiss (B73) 2013 Day (B31) 2022; 127 Guerrero (B13) 2023 Cloyd (B64) 2020 Guni (B2) 2024 Maffulli (B56) 2020 Soangra (B15) 2022 Litvin (B60) 2021 Benke (B1) 2018; 15 Tam (B58) 2008 Kitaguchi (B44) 2020; 79 Bertsimas (B77) 2018; 268 Ghannadrad (B33) 2022 Bai (B34) 2019; 7 Razis (B28) 2023 Noh (B53) 2023 Morris (B68); 89 Han (B18) 2019; 19 |
| References_xml | – year: 2022 ident: B67 article-title: Artificial intelligence and surgery: ethical dilemmas and open issues publication-title: J Am Coll Surg doi: 10.1097/XCS.0000000000000242 – year: 2022 ident: B33 article-title: Recommender systems for science: a basic taxonomy publication-title: Proceedings of the 18th Italian Research Conference on Digital Libraries (IRCDL 2022); 2022 Feb 24-25; Padua, Italy – volume: 19 start-page: 460 year: 2019 ident: B18 article-title: Medical education trends for future physicians in the era of advanced technology and artificial intelligence: an integrative review publication-title: BMC Med Educ doi: 10.1186/s12909-019-1891-5 – volume-title: International Labour Organization year: 2023 ident: B76 article-title: Generative AI and jobs: a global analysis of potential effects on job quantity and quality doi: 10.54394/FHEM8239 – ident: B23 – volume: 106 start-page: 36 year: 2018 ident: B24 article-title: A recent overview of the state-of-the-art elements of text classification publication-title: Expert Syst Appl doi: 10.1016/j.eswa.2018.03.058 – volume: 10 start-page: 390 year: 2023 ident: B29 article-title: Detection of fake papers in the era of artificial intelligence publication-title: Diagnosis doi: 10.1515/dx-2023-0090 – volume: 18 start-page: 1 year: 2023 ident: B66 article-title: Surgeons’ perspectives on artificial intelligence to support clinical decision-making in trauma and emergency contexts: results from an international survey publication-title: World J Emerg Surg doi: 10.1186/s13017-022-00467-3 – volume: 2 start-page: 122 year: 2022 ident: B7 article-title: The potential of artificial intelligence as an equalizer of gender disparity in surgical training and education publication-title: Artif Intell Surg doi: 10.20517/ais.2022.12 – volume: 273 start-page: 684 year: 2021 ident: B42 article-title: Machine learning for surgical phase recognition: a systematic review publication-title: Ann Surg doi: 10.1097/SLA.0000000000004425 – volume: 270 start-page: 414 year: 2019 ident: B47 article-title: Computer vision analysis of intraoperative video: automated recognition of operative steps in laparoscopic sleeve gastrectomy publication-title: Ann Surg doi: 10.1097/SLA.0000000000003460 – ident: B4 – ident: B30 – year: 2020 ident: B9 article-title: A vision of the use of technology in medical education after the COVID-19 pandemic publication-title: MedEdPublish (2016) doi: 10.15694/mep.2020.000049.1 – year: 2021 ident: B14 article-title: How the use of the artificial intelligence could improve surgical skills in urology: state of the art and future perspectives publication-title: Curr Opin Urol doi: 10.1097/MOU.0000000000000890 – year: 2022 ident: B15 article-title: Evaluation of surgical skill using machine learning with optimal wearable sensor locations publication-title: PLoS ONE doi: 10.1371/journal.pone.0267936 – volume: 14 start-page: 101004 year: 2020 ident: B35 article-title: Identification of highly-cited papers using topic-model-based and bibliometric features: the consideration of keyword popularity publication-title: J Informetr doi: 10.1016/j.joi.2019.101004 – year: 2022 ident: B71 article-title: Ethical risk factors and mechanisms in artificial intelligence decision making publication-title: Behav Sci (Basel) doi: 10.3390/bs12090343 – volume: 15 year: 2018 ident: B1 article-title: Artificial intelligence and big data in public health publication-title: Int J Environ Res Public Health doi: 10.3390/ijerph15122796 – volume: 89 start-page: 55 ident: B68 article-title: Ethical, legal, and financial considerations of artificial intelligence in surgery publication-title: Am Surg doi: 10.1177/00031348221117042 – year: 2023 ident: B19 article-title: Artificial intelligence teaching as part of medical education: qualitative analysis of expert interviews publication-title: JMIR Med Educ doi: 10.2196/46428 – volume: 11 start-page: e5290 year: 2023 ident: B21 article-title: Navigating the ethical landmines of ChatGPT: implications of intelligent chatbots in plastic surgery clinical practice publication-title: Plast Reconstr Surg Glob Open doi: 10.1097/GOX.0000000000005290 – year: 2022 ident: B65 article-title: Textbook outcome in hepato-pancreato-biliary surgery: systematic review publication-title: BJS Open doi: 10.1093/bjsopen/zrac149 – ident: B26 – volume: 79 start-page: 88 year: 2020 ident: B44 article-title: Automated laparoscopic colorectal surgery workflow recognition using artificial intelligence: experimental research publication-title: Int J Surg doi: 10.1016/j.ijsu.2020.05.015 – year: 2022 ident: B63 article-title: How to establish benchmarks for surgical outcomes? A checklist based on an international expert delphi consensus publication-title: Ann Surg doi: 10.1097/SLA.0000000000003931 – year: 2020 ident: B64 article-title: Comprehensive complication index validates improved outcomes over time despite increased complexity in 3707 consecutive hepatectomies publication-title: Ann Surg doi: 10.1097/SLA.0000000000003043 – year: 2021 ident: B55 article-title: Artificial intelligence and robotics in spine surgery publication-title: Global Spine J doi: 10.1177/2192568220915718 – year: 2021 ident: B50 article-title: Neurosurgery and artificial intelligence publication-title: AIMS Neurosci doi: 10.3934/Neuroscience.2021025 – year: 2020 ident: B74 article-title: Public perceptions of artificial intelligence and robotics in medicine publication-title: J Endourol doi: 10.1089/end.2020.0137 – year: 2020 ident: B49 article-title: Attitudes of patients and their relatives toward artificial intelligence in neurosurgery publication-title: World Neurosurg doi: 10.1016/j.wneu.2020.03.029 – year: 2022 ident: B10 article-title: Robotics and artificial intelligence in endovascular neurosurgery publication-title: Cureus doi: 10.7759/cureus.23662 – year: 2023 ident: B13 article-title: Advancing surgical education: the use of artificial intelligence in surgical training publication-title: Am Surg doi: 10.1177/00031348221101503 – volume: 8 start-page: 878 year: 2023 ident: B37 article-title: AI et al.: machines are about to change scientific publishing forever publication-title: ACS Energy Lett doi: 10.1021/acsenergylett.2c02828 – volume: 274 start-page: e93 year: 2021 ident: B43 article-title: A computer vision platform to automatically locate critical events in surgical videos: documenting safety in laparoscopic cholecystectomy publication-title: Ann Surg doi: 10.1097/SLA.0000000000004736 – volume: 16 start-page: 2029 year: 2021 ident: B45 article-title: Surgical workflow recognition with 3DCNN for sleeve gastrectomy publication-title: Int J Comput Assist Radiol Surg doi: 10.1007/s11548-021-02473-3 – year: 2022 ident: B20 article-title: Ensemble deep learning for the prediction of proficiency at a virtual simulator for robot-assisted surgery publication-title: Surg Endosc doi: 10.1007/s00464-021-08999-6 – volume-title: bioRxiv year: 2020 ident: B61 article-title: Combining mechanistic models and machine learning for personalized chemotherapy and surgery sequencing in breast cancer doi: 10.1007/978-3-030-64511-3_2 – year: 2022 ident: B62 article-title: Artificial intelligence applications in cardio-oncology: leveraging high dimensional cardiovascular data publication-title: Front Cardiovasc Med doi: 10.3389/fcvm.2022.941148 – volume: 7 start-page: 9324 year: 2019 ident: B34 article-title: Scientific paper recommendation: a survey publication-title: IEEE Access doi: 10.1109/ACCESS.2018.2890388 – year: 2022 ident: B48 article-title: Artificial intelligence in colorectal cancer surgery: present and future perspectives publication-title: Cancers (Basel) doi: 10.3390/cancers14153803 – year: 2024 ident: B2 article-title: Artificial intelligence in surgery: the future is now publication-title: Eur Surg Res doi: 10.1159/000536393 – year: 2023 ident: B11 article-title: Remote asynchronous feedback for unsupervised laparoscopic training: the “lapp” platform publication-title: Arq Bras Cir Dig doi: 10.1590/0102-672020220002e1712 – volume: 2 year: 2021 ident: B39 article-title: A surgeon’s guide to machine learning publication-title: Ann Surg Open doi: 10.1097/AS9.0000000000000091 – year: 2021 ident: B60 article-title: WSES project on decision support systems based on artificial neural networks in emergency surgery publication-title: World J Emerg Surg doi: 10.1186/s13017-021-00394-9 – ident: B80 – year: 2019 ident: B59 article-title: Use of artificial intelligence to represent emergent systems and augment surgical decision-making publication-title: JAMA Surg doi: 10.1001/jamasurg.2019.1510 – year: 2013 ident: B73 article-title: Risks and long-term complications of adolescent idiopathic scoliosis surgery versus non-surgical and natural history outcomes publication-title: Hard Tissue doi: 10.13172/2050-2303-2-3-498 – volume: 36 start-page: 86 year: 2017 ident: B46 article-title: Endonet: a deep architecture for recognition tasks on laparoscopic videos publication-title: IEEE Trans Med Imaging doi: 10.1109/TMI.2016.2593957 – year: 2022 ident: B12 article-title: Machine learning algorithms for predicting surgical outcomes after colorectal surgery: a systematic review publication-title: World J Surg doi: 10.1007/s00268-022-06728-1 – year: 2023 ident: B53 article-title: Artificial intelligence for neurosurgery: current state and future directions publication-title: J Korean Neurosurg Soc doi: 10.3340/jkns.2022.0130 – volume-title: Artificial Intelligence in Surgery: Understanding the Role of AI in Surgical Practice year: 2021 ident: B41 article-title: Applications of deep learning in surgery – volume: 28 start-page: 35 year: 2022 ident: B27 article-title: Benchmarking scientific image forgery detectors publication-title: Sci Eng Ethics doi: 10.1007/s11948-022-00391-4 – volume: 127 start-page: 5965 year: 2022 ident: B31 article-title: Exploratory analysis of text duplication in peer-review reveals peer-review fraud and paper mills publication-title: Scientometrics doi: 10.1007/s11192-022-04504-5 – volume: 4 start-page: 100796 year: 2023 ident: B79 article-title: Why technical solutions for detecting AI-generated content in research and education are insufficient publication-title: Patterns doi: 10.1016/j.patter.2023.100796 – volume: 37 start-page: 4 year: 2024 ident: B22 article-title: Artificial intelligence to support publishing and peer review: a summary and review publication-title: Learn Publ doi: 10.1002/leap.1570 – year: 2023 ident: B69 article-title: Ethical implications of artificial intelligence in the healthcare sector publication-title: Adv Multidiscip Sci Res J Publication – year: 2020 ident: B56 article-title: Artificial intelligence and machine learning in orthopedic surgery: a systematic review protocol publication-title: J Orthop Surg Res doi: 10.1186/s13018-020-02002-z – year: 2021 ident: B36 article-title: COPE discussion document: artificial intelligence (AI) in decision making publication-title: Committee Publication Ethics doi: 10.24318/9kvAgrnJ – year: 2018 ident: B70 article-title: Artificial intelligence in surgery: promises and perils publication-title: Ann Surg doi: 10.1097/SLA.0000000000002693 – ident: B25 – year: 2023 ident: B51 article-title: Neurosurgical management of cerebrospinal tumors in the era of artificial intelligence: a scoping review publication-title: J Korean Neurosurg Soc doi: 10.3340/jkns.2021.0213 – start-page: 1 year: 2023 ident: B28 – volume: 5 start-page: e13930 year: 2019 ident: B6 article-title: Applications and challenges of implementing artificial intelligence in medical education: integrative review publication-title: JMIR Med Educ doi: 10.2196/13930 – volume: 18 start-page: 102 year: 2024 ident: B3 article-title: Clinical applications of artificial intelligence in robotic surgery publication-title: J Robot Surg doi: 10.1007/s11701-024-01867-0 – year: 2022 ident: B52 article-title: The future of artificial intelligence in neurosurgery: a narrative review publication-title: Surg Neurol Int doi: 10.25259/SNI_877_2022 – year: 2008 ident: B58 article-title: Towards predictive, preventive, and personalized paediatric surgery publication-title: J Pediatr Surg doi: 10.1016/j.jpedsurg.2007.10.012 – volume: 89 start-page: 36 ident: B40 article-title: Deep learning applications in surgery: current uses and future directions publication-title: Am Surg doi: 10.1177/00031348221101490 – volume: 268 start-page: 574 year: 2018 ident: B77 article-title: Surgical risk is not linear: derivation and validation of a novel, user-friendly, and machine-learning-based predictive optimal trees in emergency surgery risk (POTTER) calculator publication-title: Ann Surg doi: 10.1097/SLA.0000000000002956 – volume: 232 start-page: 912 year: 2021 ident: B78 article-title: Validation of the artificial intelligence-based predictive optimal trees in emergency surgery risk (POTTER) calculator in emergency general surgery and emergency laparotomy patients publication-title: J Am Coll Surg doi: 10.1016/j.jamcollsurg.2021.02.009 – volume: 185 start-page: 120 year: 2021 ident: B32 article-title: In silico trials: verification, validation and uncertainty quantification of predictive models used in the regulatory evaluation of biomedical products publication-title: Methods doi: 10.1016/j.ymeth.2020.01.011 – year: 2019 ident: B54 article-title: Artificial intelligence in neurosurgery: a comment on the possibilities publication-title: Neurospine doi: 10.14245/ns.1938404.202 – volume: 5 year: 2023 ident: B57 article-title: A survey on detecting healthcare concept drift in AI/ML models from a finance perspective publication-title: Front Artif Intell doi: 10.3389/frai.2022.955314 – volume: 14 start-page: 5670 year: 2024 ident: B5 article-title: The model student: GPT-4 performance on graduate biomedical science exams publication-title: Sci Rep doi: 10.1038/s41598-024-55568-7 – year: 2021 ident: B17 article-title: Surgical data science and artificial intelligence for surgical education publication-title: J Surg Oncol doi: 10.1002/jso.26496 – year: 2023 ident: B16 article-title: Craniotomy simulator with force myography and machine learning-based skills assessment publication-title: Bioengineering (Basel) doi: 10.3390/bioengineering10040465 – volume: 219 start-page: 703 year: 2022 ident: B38 article-title: Artificial intelligence (AI) for lung nodules, from the AJR special series on AI applications publication-title: Am J Roentgenol doi: 10.2214/AJR.22.27487 – year: 2022 ident: B75 article-title: Integrating ethics and career futures with technical learning to promote AI literacy for middle school students: an exploratory study publication-title: Int J Artif Intell Educ doi: 10.1007/s40593-022-00293-3 – year: 2023 ident: B72 article-title: The ethics of artificial intelligence: examining the ethical considerations surrounding the development and use of AI publication-title: Am J Technol doi: 10.58425/ajt.v2i1.142 – volume: 4 year: 2022 ident: B8 article-title: The role of artificial intelligence in surgical simulation publication-title: Front Med Technol doi: 10.3389/fmedt.2022.1076755 |
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