Machine learning decision tree algorithm role for predicting mortality in critically ill adult COVID-19 patients admitted to the ICU

• Main Authors: Alyaa Elhazmi (Author), Awad Al-Omari (Author), Hend Sallam (Author), Hani N. Mufti (Author), Ahmed A. Rabie (Author), Mohammed Alshahrani (Author), Ahmed Mady (Author), Adnan Alghamdi (Author), Ali Altalaq (Author), Mohamed H. Azzam (Author), Anees Sindi (Author), Ayman Kharaba (Author), Zohair A. Al-Aseri (Author), Ghaleb A. Almekhlafi (Author), Wail Tashkandi (Author), Saud A. Alajmi (Author), Fahad Faqihi (Author), Abdulrahman Alharthy (Author), Jaffar A. Al-Tawfiq (Author), Rami Ghazi Melibari (Author), Waleed Al-Hazzani (Author), Yaseen M. Arabi (Author)
• Format: Book
• Published: Elsevier, 2022-07-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Background: Coronavirus disease-19 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is currently a major cause of intensive care unit (ICU) admissions globally. The role of machine learning in the ICU is evolving but currently limited to diagnostic and pro...