دورية أكاديمية

Strengths-weaknesses-opportunities-threats analysis of artificial intelligence in anesthesiology and perioperative medicine

التفاصيل البيبلوغرافية
العنوان: Strengths-weaknesses-opportunities-threats analysis of artificial intelligence in anesthesiology and perioperative medicine
المؤلفون: Henry J. Paiste, Ryan C. Godwin, Andrew D. Smith, Dan E. Berkowitz, Ryan L. Melvin
المصدر: Frontiers in Digital Health, Vol 6 (2024)
بيانات النشر: Frontiers Media S.A., 2024.
سنة النشر: 2024
المجموعة: LCC:Medicine
LCC:Public aspects of medicine
LCC:Electronic computers. Computer science
مصطلحات موضوعية: data science, artificial intelligence, SWOT, perioperative medicine, machine learning and AI, Medicine, Public aspects of medicine, RA1-1270, Electronic computers. Computer science, QA75.5-76.95
الوصف: The use of artificial intelligence (AI) and machine learning (ML) in anesthesiology and perioperative medicine is quickly becoming a mainstay of clinical practice. Anesthesiology is a data-rich medical specialty that integrates multitudes of patient-specific information. Perioperative medicine is ripe for applications of AI and ML to facilitate data synthesis for precision medicine and predictive assessments. Examples of emergent AI models include those that assist in assessing depth and modulating control of anesthetic delivery, event and risk prediction, ultrasound guidance, pain management, and operating room logistics. AI and ML support analyzing integrated perioperative data at scale and can assess patterns to deliver optimal patient-specific care. By exploring the benefits and limitations of this technology, we provide a basis of considerations for evaluating the adoption of AI models into various anesthesiology workflows. This analysis of AI and ML in anesthesiology and perioperative medicine explores the current landscape to understand better the strengths, weaknesses, opportunities, and threats (SWOT) these tools offer.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2673-253X
Relation: https://www.frontiersin.org/articles/10.3389/fdgth.2024.1316931/full; https://doaj.org/toc/2673-253X
DOI: 10.3389/fdgth.2024.1316931
URL الوصول: https://doaj.org/article/486fc3fc65d340cb93666abd8322b67e
رقم الأكسشن: edsdoj.486fc3fc65d340cb93666abd8322b67e
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:2673253X
DOI:10.3389/fdgth.2024.1316931