Risk estimation for the primary prevention of cardiovascular disease: considerations for appropriate risk prediction model selection
KR van Daalen, D Zhang, S Kaptoge… - The Lancet Global …, 2024 - thelancet.com
Cardiovascular diseases remain the number one cause of death globally. Cardiovascular
disease risk scores are an integral tool in primary prevention, being used to identify …
disease risk scores are an integral tool in primary prevention, being used to identify …
Prognosticating the outcome of intensive care in older patients—a narrative review
M Beil, R Moreno, J Fronczek, Y Kogan… - Annals of Intensive …, 2024 - Springer
Prognosis determines major decisions regarding treatment for critically ill patients. Statistical
models have been developed to predict the probability of survival and other outcomes of …
models have been developed to predict the probability of survival and other outcomes of …
Robust and consistent biomarker candidates identification by a machine learning approach applied to pancreatic ductal adenocarcinoma metastasis
T Mahawan, T Luckett, A Mielgo Iza… - BMC Medical Informatics …, 2024 - Springer
Abstract Background Machine Learning (ML) plays a crucial role in biomedical research.
Nevertheless, it still has limitations in data integration and irreproducibility. To address these …
Nevertheless, it still has limitations in data integration and irreproducibility. To address these …
Evaluation of Predictive Reliability to Foster Trust in Artificial Intelligence. A case study in Multiple Sclerosis
Applying Artificial Intelligence (AI) and Machine Learning (ML) in critical contexts, such as
medicine, requires the implementation of safety measures to reduce risks of harm in case of …
medicine, requires the implementation of safety measures to reduce risks of harm in case of …
Bayesian Networks in the Management of Hospital Admissions: A Comparison between Explainable AI and Black Box AI during the Pandemic
Artificial Intelligence (AI) and Machine Learning (ML) approaches that could learn from large
data sources have been identified as useful tools to support clinicians in their decisional …
data sources have been identified as useful tools to support clinicians in their decisional …
Sample size for developing a prediction model with a binary outcome: targeting precise individual risk estimates to improve clinical decisions and fairness
When developing a clinical prediction model, the sample size of the development dataset is
a key consideration. Small sample sizes lead to greater concerns of overfitting, instability …
a key consideration. Small sample sizes lead to greater concerns of overfitting, instability …
Speculations on Uncertainty and Humane Algorithms
N Gray - arXiv preprint arXiv:2408.06736, 2024 - arxiv.org
The appreciation and utilisation of risk and uncertainty can play a key role in helping to solve
some of the many ethical issues that are posed by AI. Understanding the uncertainties can …
some of the many ethical issues that are posed by AI. Understanding the uncertainties can …
Development and validation of a novel clinical risk score to predict hypoxemia in children with pneumonia using the WHO PREPARE dataset
Background Hypoxemia predicts mortality at all levels of care, and appropriate management
can reduce preventable deaths. However, pulse oximetry and oxygen therapy remain …
can reduce preventable deaths. However, pulse oximetry and oxygen therapy remain …
Development and Validation of a Diagnostic Prediction Rule for Osteopenia
T Janwittayanuchit, N Kaewboonlert… - medRxiv, 2024 - medrxiv.org
Objectives To triage patients with a high likelihood of osteopenia before referring them for a
standard bone mass density test for diagnosis. Introduction Osteopenia defined by low bone …
standard bone mass density test for diagnosis. Introduction Osteopenia defined by low bone …
Bedside variables to guide decision-making in critically ill patients
E Cox - 2024 - research.rug.nl
Patients admitted to the intensive care unit (ICU) suffer from various diseases and
comorbidities. Only critically ill patients that require continuous care, organ support, or …
comorbidities. Only critically ill patients that require continuous care, organ support, or …