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Fung E, Patel D, Tatum S. Artificial intelligence in maxillofacial and facial plastic and reconstructive surgery. Curr Opin Otolaryngol Head Neck Surg 2024; 32:257-262. [PMID: 38837245 DOI: 10.1097/moo.0000000000000983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2024]
Abstract
PURPOSE OF REVIEW To provide a current review of artificial intelligence and its subtypes in maxillofacial and facial plastic surgery including a discussion of implications and ethical concerns. RECENT FINDINGS Artificial intelligence has gained popularity in recent years due to technological advancements. The current literature has begun to explore the use of artificial intelligence in various medical fields, but there is limited contribution to maxillofacial and facial plastic surgery due to the wide variance in anatomical facial features as well as subjective influences. In this review article, we found artificial intelligence's roles, so far, are to automatically update patient records, produce 3D models for preoperative planning, perform cephalometric analyses, and provide diagnostic evaluation of oropharyngeal malignancies. SUMMARY Artificial intelligence has solidified a role in maxillofacial and facial plastic surgery within the past few years. As high-quality databases expand with more patients, the role for artificial intelligence to assist in more complicated and unique cases becomes apparent. Despite its potential, ethical questions have been raised that should be noted as artificial intelligence continues to thrive. These questions include concerns such as compromise of the physician-patient relationship and healthcare justice.
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Affiliation(s)
| | | | - Sherard Tatum
- Department of Otolaryngology
- Department of Pediatrics, SUNY Upstate Medical University, Syracuse, New York, USA
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2
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Anand K, Hong S, Anand K, Hendrix J. Machine learning: implications and applications for ambulatory anesthesia. Curr Opin Anaesthesiol 2024:00001503-990000000-00215. [PMID: 38979675 DOI: 10.1097/aco.0000000000001410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
PURPOSE OF REVIEW This review explores the timely and relevant applications of machine learning in ambulatory anesthesia, focusing on its potential to optimize operational efficiency, personalize risk assessment, and enhance patient care. RECENT FINDINGS Machine learning models have demonstrated the ability to accurately forecast case durations, Post-Anesthesia Care Unit (PACU) lengths of stay, and risk of hospital transfers based on preoperative patient and procedural factors. These models can inform case scheduling, resource allocation, and preoperative evaluation. Additionally, machine learning can standardize assessments, predict outcomes, improve handoff communication, and enrich patient education. SUMMARY Machine learning has the potential to revolutionize ambulatory anesthesia practice by optimizing efficiency, personalizing care, and improving quality and safety. However, limitations such as algorithmic opacity, data biases, reproducibility issues, and adoption barriers must be addressed through transparent, participatory design principles and ongoing validation to ensure responsible innovation and incremental adoption.
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Affiliation(s)
| | - Suk Hong
- Department of Anesthesiology and Pain Management
| | - Kapil Anand
- University of Texas Southwestern, Department of Anesthesiology and Pain Management, Dallas
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Berger-Estilita J, Marcolino I, Radtke FM. Patient-centered precision care in anaesthesia - the PC-square (PC) 2 approach. Curr Opin Anaesthesiol 2024; 37:163-170. [PMID: 38284262 PMCID: PMC10911256 DOI: 10.1097/aco.0000000000001343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2024]
Abstract
PURPOSE OF REVIEW This review navigates the landscape of precision anaesthesia, emphasising tailored and individualized approaches to anaesthetic administration. The aim is to elucidate precision medicine principles, applications, and potential advancements in anaesthesia. The review focuses on the current state, challenges, and transformative opportunities in precision anaesthesia. RECENT FINDINGS The review explores evidence supporting precision anaesthesia, drawing insights from neuroscientific fields. It probes the correlation between high-dose intraoperative opioids and increased postoperative consumption, highlighting how precision anaesthesia, especially through initiatives like Safe Brain Initiative (SBI), could address these issues. The SBI represents multidisciplinary collaboration in perioperative care. SBI fosters effective communication among surgical teams, anaesthesiologists, and other medical professionals. SUMMARY Precision anaesthesia tailors care to individual patients, incorporating genomic insights, personalised drug regimens, and advanced monitoring techniques. From EEG to cerebral/somatic oximetry, these methods enhance precision. Standardised reporting, patient-reported outcomes, and continuous quality improvement, alongside initiatives like SBI, contribute to improved patient outcomes. Precision anaesthesia, underpinned by collaborative programs, emerges as a promising avenue for enhancing perioperative care.
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Affiliation(s)
- Joana Berger-Estilita
- Institute of Anaesthesiology and Intensive Care, Salemspital, Hirslanden Medical Group
- Institute for Medical Education, University of Bern, Bern, Switzerland
- CINTESIS - Center for Health Technology and Services Research, Faculty of Medicine, Porto, Portugal
| | - Isabel Marcolino
- Institute of Anaesthesiology and Intensive Care, Spital Limmattal, Schlieren, Switzerland
| | - Finn M. Radtke
- Department of Anaesthesia and Intensive Care, Hospital of Nykøbing Falster, University of Southern Denmark, Odense, Denmark
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Cavaliere F, Allegri M, Apan A, Brazzi L, Carassiti M, Cohen E, DI Marco P, Langeron O, Rossi M, Spieth P, Turnbull D, Weber F. A year in review in Minerva Anestesiologica 2023: anesthesia, analgesia, and perioperative medicine. Minerva Anestesiol 2024; 90:222-234. [PMID: 38535972 DOI: 10.23736/s0375-9393.24.18067-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Affiliation(s)
- Franco Cavaliere
- IRCCS A. Gemelli University Polyclinic Foundation, Sacred Heart Catholic University, Rome, Italy -
| | - Massimo Allegri
- Lemanic Center of Analgesia and Neuromodulation EHC, Morges, Switzerland
| | - Alparslan Apan
- Department of Anesthesiology and Intensive Care, Faculty of Medicine, University of Giresun, Giresun, Türkiye
| | - Luca Brazzi
- Department of Surgical Sciences, University of Turin, Turin, Italy
| | - Massimiliano Carassiti
- Unit of Anesthesia, Intensive Care and Pain Management, Campus Bio-Medico University Hospital, Rome, Italy
| | - Edmond Cohen
- Department of Anesthesiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Pierangelo DI Marco
- Department of Cardiovascular, Respiratory, Nephrologic, Anesthesiologic, and Geriatric Sciences, Faculty of Medicine, Sapienza University, Rome, Italy
| | - Olivier Langeron
- Department of Anesthesia and Intensive Care, Henri Mondor University Hospital, Assistance Publique - Hôpitaux de Paris (APHP), University Paris-Est Créteil (UPEC), Paris, France
| | - Marco Rossi
- IRCCS A. Gemelli University Polyclinic Foundation, Sacred Heart Catholic University, Rome, Italy
| | - Peter Spieth
- Department of Anesthesiology and Critical Care Medicine, University Hospital of Dresden, Dresden, Germany
| | - David Turnbull
- Department of Anesthetics and Neuro Critical Care, Royal Hallamshire Hospital, Sheffield, UK
| | - Frank Weber
- Department of Anesthesiology, Sophia Children's Hospital, Erasmus University Medical Center, Rotterdam, the Netherlands
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Bastola P, Atreya A, Bhandari PS, Parajuli S. The evolution of anesthesiology education: Embracing new technologies and teaching approaches. Health Sci Rep 2024; 7:e1765. [PMID: 38299206 PMCID: PMC10825374 DOI: 10.1002/hsr2.1765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 11/06/2023] [Accepted: 11/28/2023] [Indexed: 02/02/2024] Open
Abstract
Background and aims Medical education requires regular reforms to include emerging best practices and technologies, while also critically evaluating effectiveness of traditional didactic teaching methods. This manuscript examines the challenges and opportunities associated with modernizing the anesthesiology curriculum. Methods Narrative review of literature on innovations in medical education, with a specific emphasis on anesthesiology training. Results Educators face difficulties implementing new teaching approaches and evaluating their effectiveness. However, active learning methods, blended with selected traditional techniques, can enhance learner engagement and competencies. Self-directed learning and simulations prepare students for real-world practice, while flipped classrooms and online platforms increase accessibility. Conclusions A blended approach, integrating interactive technology alongside modified lectures and seminars, may optimize anesthesiology education. Despite the promise of improved pedagogies, further research is required to assess outcomes. By embracing innovation while retaining certain foundational methods, programs can equip anesthesiologists with modern skills. This evolution is key to meeting the needs of 21st-century anesthesia care needs. Remaining at the forefront of this transformation will be vital in preparing competent future anesthesiologists through state-of-the-art education.
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Affiliation(s)
- Priska Bastola
- Department of Cardiothoracic and Vascular Anaesthesiology, Manmohan Cardiothoracic and Vascular Center, Maharajgunj Medical Campus, Institute of MedicineTribhuvan UniversityKathmanduNepal
| | - Alok Atreya
- Department of Forensic MedicineLumbini Medical CollegePalpaNepal
| | - Prawesh S. Bhandari
- Department of Orthopedics, Maharajgunj Medical Campus, Institute of MedicineTribhuvan University Teaching Hospital, Tribhuvan UniversityKathmanduNepal
| | - Subigya Parajuli
- Research Program Coordinator, Department of Surgery and Perioperative CareThe University of TexasAustinTexasUSA
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Singam A. Revolutionizing Patient Care: A Comprehensive Review of Artificial Intelligence Applications in Anesthesia. Cureus 2023; 15:e49887. [PMID: 38174199 PMCID: PMC10762564 DOI: 10.7759/cureus.49887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 12/03/2023] [Indexed: 01/05/2024] Open
Abstract
This review explores the intersection of artificial intelligence (AI) and anesthesia, examining its transformative impact on patient care across various phases. Beginning with a historical overview of anesthesia, we highlight the critical role of technological advancements in ensuring optimal patient outcomes. The emergence of AI in healthcare sets the stage for a comprehensive analysis of its applications in anesthesia. In the preoperative phase, AI facilitates personalized risk assessments and decision support, optimizing anesthesia planning and drug dosage predictions. Moving to the intraoperative phase, we delve into AI's role in monitoring and control through sophisticated anesthesia monitoring and closed-loop systems. Additionally, we discuss the integration of robotics and AI-guided procedures, revolutionizing surgical assistance. Transitioning to the postoperative phase, we explore AI-driven postoperative monitoring, predictive analysis for complications, and the integration of AI into rehabilitation programs and long-term follow-up. These new applications redefine patient recovery, emphasizing personalized care and proactive interventions. However, the integration of AI in anesthesia poses challenges and ethical considerations. Data security, interpretability, and bias in AI algorithms demand scrutiny. Moreover, the evolving patient-doctor relationship in an AI-driven care landscape requires a delicate balance between efficiency and human touch. Looking forward, we discuss the future directions of AI in anesthesia, anticipating advances in technology and AI algorithms. The integration of AI into routine clinical practice and its potential impact on anesthesia education and training are explored, emphasizing the need for collaboration, education, and ethical guidelines. This review provides a comprehensive overview of AI applications in anesthesia, offering insights into the present landscape, challenges, and future directions. The synthesis of historical perspectives, current applications, and future possibilities underscores the transformative potential of AI in revolutionizing patient care within the dynamic field of anesthesia.
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Affiliation(s)
- Amol Singam
- Critical Care Medicine, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
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Garg R. Medical science, technology and digital health - Need for holistic integration. Indian J Anaesth 2023; 67:851-852. [PMID: 38044919 PMCID: PMC10691605 DOI: 10.4103/ija.ija_984_23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 10/11/2023] [Accepted: 10/11/2023] [Indexed: 12/05/2023] Open
Affiliation(s)
- Rakesh Garg
- Editor-in-Chief, Indian Journal of Anaesthesia, MD, DNB, FICCM, FICA, PGCCHM, MNAMS, CCEPC, FIMSA, Fellowship in Palliative Medicine, Fellowship in Clinical Research Methodology and Evidence-Based Medicine, Professor, Department of Onco-Anaesthesia and Palliative Medicine, Dr B.R. Ambedkar Institute Rotary Cancer Hospital and National Cancer Institute, All India Institute of Medical Sciences, New Delhi, India
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Karmakar A, Khan MJ, Abdul-Rahman MEF, Shahid U. The Advances and Utility of Artificial Intelligence and Robotics in Regional Anesthesia: An Overview of Recent Developments. Cureus 2023; 15:e44306. [PMID: 37779803 PMCID: PMC10535025 DOI: 10.7759/cureus.44306] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/29/2023] [Indexed: 10/03/2023] Open
Abstract
The integration of artificial intelligence (AI) and robotics in regional anesthesia has brought about transformative changes in acute pain management for surgical procedures. This review explores the evolving landscape of AI and robotics applications in regional anesthesia, outlining their potential benefits, challenges, and ethical considerations. AI-driven pain assessment, real-time guidance for needle placement during nerve blocks, and predictive modeling solutions for nerve blocks have the potential to enhance procedural precision and improve patient outcomes. Robotic technology aids in accurate needle insertion, reducing complications and improving pain relief. This review also highlights the ethical and safety considerations surrounding AI implementation, emphasizing data security and professional training. While challenges such as costs and regulatory hurdles exist, ongoing research and clinical trials demonstrate the practical utility of these technologies. In conclusion, AI and robotics have the potential to reshape regional anesthesia practice, ultimately improving patient care and procedural accuracy in pain management.
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Affiliation(s)
- Arunabha Karmakar
- Anesthesiology and Critical Care, Hamad Medical Corporation, Doha, QAT
| | | | | | - Umair Shahid
- Anesthesiology and Critical Care, Hamad Medical Corporation, Doha, QAT
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Khan MJ, Karmakar A. Emerging Robotic Innovations and Artificial Intelligence in Endotracheal Intubation and Airway Management: Current State of the Art. Cureus 2023; 15:e42625. [PMID: 37641747 PMCID: PMC10460626 DOI: 10.7759/cureus.42625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/28/2023] [Indexed: 08/31/2023] Open
Abstract
Robotic sciences have rapidly advanced and revolutionized various aspects of medicine, including the field of airway management. Robotic endotracheal intubation is an innovative method that utilizes robotic systems to aid in the accurate placement of an endotracheal tube within the trachea. This cutting-edge technique shows great promise in improving procedural precision and ensuring patient safety. In this comprehensive overview, we delve into the present status of robotic-assisted endotracheal intubation, examining its advantages, obstacles, and the potential implications it holds for the future. In addition, this review encompasses a comprehensive analysis of the existing literature and references on recent advances in robotic technology and artificial intelligence related to airway management.
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Affiliation(s)
| | - Arunabha Karmakar
- Anesthesiology and Perioperative Medicine, Hamad Medical Corporation, Doha, QAT
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