Poor handling of continuous predictors in clinical prediction models using logistic regression: a systematic review
Background When developing a clinical prediction model, assuming a linear relationship
between the continuous predictors and outcome is not recommended. Incorrect specification …
between the continuous predictors and outcome is not recommended. Incorrect specification …
Machine learning applications in healthcare: The state of knowledge and future directions
Detection of easily missed hidden patterns with fast processing power makes machine
learning (ML) indispensable to today's healthcare system. Though many ML applications …
learning (ML) indispensable to today's healthcare system. Though many ML applications …
Personalized predictive models for symptomatic COVID-19 patients using basic preconditions: hospitalizations, mortality, and the need for an ICU or ventilator
S Wollenstein-Betech, CG Cassandras… - International Journal of …, 2020 - Elsevier
Background The rapid global spread of the SARS-CoV-2 virus has provoked a spike in
demand for hospital care. Hospital systems across the world have been over-extended …
demand for hospital care. Hospital systems across the world have been over-extended …
Using machine learning analysis to assist in differentiating between necrotizing enterocolitis and spontaneous intestinal perforation: A novel predictive analytic tool
Purpose Necrotizing enterocolitis (NEC) and spontaneous intestinal perforation (SIP) are
devastating diseases in preterm neonates, often requiring surgical treatment. Previous …
devastating diseases in preterm neonates, often requiring surgical treatment. Previous …
[HTML][HTML] A computer-assisted system for early mortality risk prediction in patients with traumatic brain injury using artificial intelligence algorithms in emergency room …
KC Tu, TT Eric Nyam, CC Wang, NC Chen, KT Chen… - Brain sciences, 2022 - mdpi.com
Traumatic brain injury (TBI) remains a critical public health challenge. Although studies have
found several prognostic factors for TBI, a useful early predictive tool for mortality has yet to …
found several prognostic factors for TBI, a useful early predictive tool for mortality has yet to …
[HTML][HTML] Classifying early infant feeding status from clinical notes using natural language processing and machine learning
The objective of this study is to develop and evaluate natural language processing (NLP)
and machine learning models to predict infant feeding status from clinical notes in the Epic …
and machine learning models to predict infant feeding status from clinical notes in the Epic …
Effect of particle size on magnesite flotation based on kinetic studies and machine learning simulation
Y Fu, B Yang, Y Ma, Q Sun, J Yao, W Fu, W Yin - Powder Technology, 2020 - Elsevier
This research focused on the effect of particle size and flotation time on magnesite flotation,
and the flotation performance of various size fractions were predicted by a machine learning …
and the flotation performance of various size fractions were predicted by a machine learning …
Machine learning meets cancer
EV Varlamova, MA Butakova, VV Semyonova… - Cancers, 2024 - mdpi.com
Simple Summary This review examines the latest technologies using machine learning (ML)
methods, including the use of convolutional neural networks, decision trees, and generative …
methods, including the use of convolutional neural networks, decision trees, and generative …
Feature selection and predicting chemotherapy-induced ulcerative mucositis using machine learning methods
PS Satheeshkumar, M El-Dallal, MP Mohan - International Journal of …, 2021 - Elsevier
Objective Ulcerative mucositis (UM) is a devastating complication of most cancer therapies
with less recognized risk factors. Whilst risk predictions are most vital in adverse events, we …
with less recognized risk factors. Whilst risk predictions are most vital in adverse events, we …
[HTML][HTML] AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data
Background Medical decision-making impacts both individual and public health. Clinical
scores are commonly used among various decision-making models to determine the degree …
scores are commonly used among various decision-making models to determine the degree …