Leading in the development, standardised evaluation, and adoption of artificial intelligence in clinical practice: regional anaesthesia as an example

被引:1
|
作者
Bowness, James S. [1 ,2 ]
Liu, Xiaoxuan [3 ,4 ]
Keane, Pearse A. [5 ,6 ]
机构
[1] Univ Oxford, Nuffield Dept Clin Anaesthesia, Oxford, England
[2] Aneurin Bevan Univ Hlth Board, Dept Anaesthesia, Newport, Wales
[3] Univ Hosp Birmingham NHS Fdn Trust, Birmingham, England
[4] Univ Birmingham, Coll Med & Dent Sci, Birmingham, England
[5] UCL, Inst Ophthalmol, Fac Brain Sci, London, England
[6] Moorfields Eye Hosp NHS Fdn Trust, NIHR Biomed Res Ctr, London, England
关键词
artificial intelligence; regional anaesthesia; ultrasound; evaluation; medical devices; regulation; standardisation; AMERICAN SOCIETY; PAIN MEDICINE; EDUCATION;
D O I
10.1016/j.bja.2023.12.024
中图分类号
R614 [麻醉学];
学科分类号
100217 ;
摘要
A recent study by Suissa and colleagues explored the clinical relevance of a medical image segmentation metric (Dice metric) commonly used in the field of artificial intelligence (AI). They showed that pixel-wise agreement for physician identification of structures on ultrasound images is variable, and a relatively low Dice metric (0.34) correlated to a substantial agreement on subjective clinical assessment. We highlight the need to bring structure and clinical perspective to the evaluation of medical AI, which clinicians are best placed to direct.
引用
收藏
页码:1016 / 1021
页数:6
相关论文
共 50 条
  • [21] How will clinical practice be impacted by artificial intelligence?
    Jacques Biot
    European Journal of Dermatology, 2019, 29 : 8 - 10
  • [22] Development and evaluation of an artificial intelligence for bacterial growth monitoring in clinical bacteriology
    Jacot, Damien
    Gizha, Shklqim
    Orny, Cedrick
    Fernandes, Mathieu
    Tricoli, Carmelo
    Marcelpoil, Raphael
    Prod'hom, Guy
    Volle, Jean-Marc
    Greub, Gilbert
    Croxatto, Antony
    JOURNAL OF CLINICAL MICROBIOLOGY, 2024, 62 (05)
  • [23] Clinical Evaluation of Artificial Intelligence-Enabled Interventions
    Hogg, H. D. Jeffry
    Martindale, Alexander P. L.
    Liu, Xiaoxuan
    Denniston, Alastair K.
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2024, 65 (10)
  • [24] The Adoption of Artificial Intelligence in Serbian Hospitality: A Potential Path to Sustainable Practice
    Gajic, Tamara
    Vukolic, Dragan
    Bugarcic, Jovan
    Dokovic, Filip
    Spasojevic, Ana
    Knezevic, Snezana
    Boljanovic, Jelena Dordevic
    Glisic, Slobodan
    Matovic, Stefana
    David, Lorant Denes
    SUSTAINABILITY, 2024, 16 (08)
  • [25] How will clinical practice be impacted by artificial intelligence?
    Biot, Jacques
    EUROPEAN JOURNAL OF DERMATOLOGY, 2019, 29 (Suppl 1) : 8 - 10
  • [26] Clinical perspectives on the adoption of the artificial intelligence-enabled electrocardiogram
    Khurshid, Shaan
    JOURNAL OF ELECTROCARDIOLOGY, 2023, 81 : 142 - 145
  • [27] Artificial Intelligence in Medicine: Chances and Challenges for Wide Clinical Adoption
    Varghese, Julian
    VISCERAL MEDICINE, 2020, 36 (06) : 443 - 449
  • [28] A multinational study on artificial intelligence adoption: Clinical implementers' perspectives
    Marco-Ruiz, Luis
    Hernandez, Miguel Angel Tejedor
    Ngo, Phuong Dinh
    Makhlysheva, Alexandra
    Svenning, Therese Olsen
    Dyb, Kari
    Chomutare, Taridzo
    Llatas, Carlos Fernandez
    Munoz-Gama, Jorge
    Tayefi, Maryam
    INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2024, 184
  • [29] Guidelines on clinical research evaluation of artificial intelligence in ophthalmology (2023)
    Yang, Wei-Hua
    Shao, Yi
    Xu, Yan-Wu
    INTERNATIONAL JOURNAL OF OPHTHALMOLOGY, 2023, 16 (09) : 1361 - 1372
  • [30] Leveraging artificial intelligence for regional anesthesiology curriculum development
    Nanda, Monika
    Grant, Stuart Alan
    REGIONAL ANESTHESIA AND PAIN MEDICINE, 2024,