Artificial intelligence, machine learning, and deep learning for clinical outcome prediction
AI is a broad concept, grouping initiatives that use a computer to perform tasks that would
usually require a human to complete. AI methods are well suited to predict clinical outcomes …
usually require a human to complete. AI methods are well suited to predict clinical outcomes …
XGBoost machine learning algorism performed better than regression models in predicting mortality of moderate-to-severe traumatic brain injury
R Wang, L Wang, J Zhang, M He, J Xu - World Neurosurgery, 2022 - Elsevier
Background Traumatic brain injury (TBI) brings severe mortality and morbidity risk to
patients. Predicting the outcome of these patients is necessary for physicians to make …
patients. Predicting the outcome of these patients is necessary for physicians to make …
State-of-the-art application of artificial intelligence to transporter-centered functional and pharmaceutical research
Protein transporters not only have essential functions in regulating the transport of
endogenous substrates and remote communication between organs and organisms, but …
endogenous substrates and remote communication between organs and organisms, but …
[HTML][HTML] Predicting outcome of traumatic brain injury: is machine learning the best way?
R Bruschetta, G Tartarisco, LF Lucca, E Leto, M Ursino… - Biomedicines, 2022 - mdpi.com
One of the main challenges in traumatic brain injury (TBI) patients is to achieve an early and
definite prognosis. Despite the recent development of algorithms based on artificial …
definite prognosis. Despite the recent development of algorithms based on artificial …
Use of random forest machine learning algorithm to predict short term outcomes following posterior cervical decompression with instrumented fusion
A Cabrera, A Bouterse, M Nelson, J Razzouk… - Journal of Clinical …, 2023 - Elsevier
Random Forest (RF) is a widely used machine learning algorithm that can be utilized for
identification of patient characteristics important for outcome prediction. Posterior cervical …
identification of patient characteristics important for outcome prediction. Posterior cervical …
Machine learning predictive models in neurosurgery: an appraisal based on the TRIPOD guidelines. Systematic review
A Warman, AL Kalluri, TD Azad - Neurosurgical Focus, 2023 - thejns.org
OBJECTIVE In recent years, machine learning models for clinical prediction have become
increasingly prevalent in the neurosurgical literature. However, little is known about the …
increasingly prevalent in the neurosurgical literature. However, little is known about the …
[HTML][HTML] MRI radiomics features from infarction and cerebrospinal fluid for prediction of cerebral edema after acute ischemic stroke
L Jiang, C Zhang, S Wang, Z Ai, T Shen… - Frontiers in Aging …, 2022 - frontiersin.org
Neuroimaging biomarkers that predict the edema after acute stroke may help clinicians
provide targeted therapies and minimize the risk of secondary injury. In this study, we …
provide targeted therapies and minimize the risk of secondary injury. In this study, we …
Classification and Regression Tree Predictive Model for Acute Kidney Injury in Traumatic Brain Injury Patients
R Wang, J Zhang, M He, J Xu - Therapeutics and Clinical Risk …, 2024 - Taylor & Francis
Background Acute kidney injury (AKI) is prevalent in hospitalized patients with traumatic
brain injury (TBI), and increases the risk of poor outcomes. We designed this study to …
brain injury (TBI), and increases the risk of poor outcomes. We designed this study to …
[HTML][HTML] Learning models for traumatic brain injury mortality prediction on pediatric electronic health records
J Fonseca, X Liu, HP Oliveira, T Pereira - Frontiers in neurology, 2022 - frontiersin.org
Background Traumatic Brain Injury (TBI) is one of the leading causes of injury related
mortality in the world, with severe cases reaching mortality rates of 30-40%. It is highly …
mortality in the world, with severe cases reaching mortality rates of 30-40%. It is highly …
Artificial Intelligence and Machine Learning Applications in Critically Ill Brain Injured Patients
JR Vitt, S Mainali - Seminars in Neurology, 2024 - thieme-connect.com
The utilization of Artificial Intelligence (AI) and Machine Learning (ML) is paving the way for
significant strides in patient diagnosis, treatment, and prognostication in neurocritical care …
significant strides in patient diagnosis, treatment, and prognostication in neurocritical care …