The artificial intelligence evidence-based medicine pyramid

Several studies exist in the literature regarding the exploitation of artificial intelligence in intensive care. However, an important gap between clinical research and daily clinical practice still exists that can only be bridged by robust validation studies carried out by multidisciplinary teams.

[1]  Ying Su,et al.  Data science in the intensive care unit , 2022, World journal of critical care medicine.

[2]  A. Freyrie,et al.  Artificial Intelligence Is the Future of Surgical Departments … Are We Ready? , 2022, Angiology.

[3]  G. Lip,et al.  Bridging the Gap Between Artificial Intelligence Research and Clinical Practice in Cardiovascular Science: What the Clinician Needs to Know , 2022, Arrhythmia & electrophysiology review.

[4]  E. Pikoulis,et al.  The Use of the Hypotension Prediction Index Integrated in an Algorithm of Goal Directed Hemodynamic Treatment during Moderate and High-Risk Surgery , 2021, Journal of clinical medicine.

[5]  D. Gommers,et al.  Moving from bytes to bedside: a systematic review on the use of artificial intelligence in the intensive care unit , 2021, Intensive Care Medicine.

[6]  E. Mascha,et al.  Hypotension Prediction Index for Prevention of Hypotension during Moderate- to High-risk Noncardiac Surgery , 2020, Anesthesiology.

[7]  Treena S. Basu,et al.  Artificial Intelligence: How is It Changing Medical Sciences and Its Future? , 2020, Indian journal of dermatology.

[8]  M. P. Mulder,et al.  Effect of a Machine Learning-Derived Early Warning System for Intraoperative Hypotension vs Standard Care on Depth and Duration of Intraoperative Hypotension During Elective Noncardiac Surgery: The HYPE Randomized Clinical Trial. , 2020, JAMA.

[9]  T. Scheeren,et al.  Ability of an Arterial Waveform Analysis–Derived Hypotension Prediction Index to Predict Future Hypotensive Events in Surgical Patients , 2020, Anesthesia and analgesia.

[10]  Mark Hoogendoorn,et al.  Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy , 2020, Intensive Care Medicine.