Machine Learning Approaches-Driven for Mortality Prediction for Patients Undergoing Craniotomy in ICU
Author:
Affiliation:
1. Surgical Intensive Care Unit, Fujian Provincial Hospital, Fujian, China
2. College of Life Science and Bioengineering, Beijing University of Technology, Beijing, China
3. Yidu Cloud (Beijing) Technology Co. Ltd, Beijing, China
Funder
National Natural Science Foundation of China
Fujian Province Intensive Medical Center Construction Project
Publisher
Informa UK Limited
Subject
Neurology (clinical),Neuroscience (miscellaneous),Developmental and Educational Psychology
Link
https://www.tandfonline.com/doi/pdf/10.1080/02699052.2021.2008491
Reference44 articles.
1. Routine use of postoperative ICU care for elective craniotomy: a cost-benefit analysis
2. Outcome following decompressive craniectomy for malignant swelling due to severe head injury
3. Complications of decompressive craniectomy for traumatic brain injury
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1. Artificial Intelligence-Enhanced Neurocritical Care for Traumatic Brain Injury : Past, Present and Future;Journal of Korean Neurosurgical Society;2024-09-01
2. A data-driven medical knowledge discovery framework to predict the length of ICU stay for patients undergoing craniotomy based on electronic medical records;Mathematical Biosciences and Engineering;2022
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