التفاصيل البيبلوغرافية
| العنوان: |
Strengths-weaknesses-opportunities-threats analysis of artificial intelligence in anesthesiology and perioperative medicine. |
| المؤلفون: |
Paiste, Henry J., Godwin, Ryan C., Smith, Andrew D., Berkowitz, Dan E., Melvin, Ryan L. |
| المصدر: |
Frontiers in Digital Health; 2024, p1-7, 7p |
| مصطلحات موضوعية: |
RISK assessment, PULMONARY embolism, LANGUAGE & languages, ARTIFICIAL intelligence, ULTRASONIC imaging, DECISION making, DECISION making in clinical medicine, PAIN management, PHYSICIAN-patient relations, ANESTHESIOLOGY, MACHINE learning, INDIVIDUALIZED medicine, PERIOPERATIVE care, OPERATING rooms, ALGORITHMS |
| مستخلص: |
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. [ABSTRACT FROM AUTHOR] |
|
Copyright of Frontiers in Digital Health is the property of Frontiers Media S.A. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| قاعدة البيانات: |
Complementary Index |
