Machine Learning as Our Weapon to Become Anesthesiologist 5.0 - Ratumasa, Marilaeta Cindryani Ra; Sucandra, MA Kresna; Aryasa, Tjahya; Sutawan, IB Krisna Jaya (Majalah Anestesia & Critical Care, 2023)
Machine learning is one of the most renowned things that have emerged in the last five years in medicine. The machine is made as if it has the cognitive ability to think independently, is able to distinguish incoming inputs and get the desired output. Along with the development of statistical and computer science, machine learning has evolved into a distinct subfield within the broader domain of data science, with far-reaching implications for various sectors, including healthcare. In medical science, technology and artificial intelligence are starting to take over anesthetic services. This paradigm shift necessitates a fundamental change in the role of future anesthesiologists A future anesthesiologist will need to continuously monitor and evaluate the performance of data science and artificial intelligence systems, and make adjustments when necessary to improve impact on patient care and outcomes. Anesthesiologists of the future will need to harness the power of data science and artificial intelligence to enhance patient care continually, emphasizing adaptability and collaboration as key elements in delivering improved healthcare outcomes.