AIMC Topic: Risk Assessment

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Detection of Extraprostatic Extension of Cancer on Biparametric MRI Combining Texture Analysis and Machine Learning: Preliminary Results.

Academic radiology
RATIONALE AND OBJECTIVES: Extraprostatic extension of disease (EPE) has a major role in risk stratification of prostate cancer patients. Currently, pretreatment local staging is performed with MRI, while the gold standard is represented by histopatho...

Real-time crash prediction models: State-of-the-art, design pathways and ubiquitous requirements.

Accident; analysis and prevention
Proactive traffic safety management systems can monitor traffic conditions in real-time, identify the formation of unsafe traffic dynamics, and implement suitable interventions to bring unsafe conditions back to normal traffic situations. Recent adva...

Machine learning in suicide science: Applications and ethics.

Behavioral sciences & the law
For decades, our ability to predict suicide has remained at near-chance levels. Machine learning has recently emerged as a promising tool for advancing suicide science, particularly in the domain of suicide prediction. The present review provides an ...

Prediction of implantation after blastocyst transfer in in vitro fertilization: a machine-learning perspective.

Fertility and sterility
OBJECTIVE: To develop a random forest model (RFM) to predict implantation potential of a transferred embryo and compare it with a multivariate logistic regression model (MvLRM), based on data from a large cohort including in vitro fertilization (IVF)...

Machine learning methodologies versus cardiovascular risk scores, in predicting disease risk.

BMC medical research methodology
BACKGROUND: The use of Cardiovascular Disease (CVD) risk estimation scores in primary prevention has long been established. However, their performance still remains a matter of concern. The aim of this study was to explore the potential of using ML m...

Primary Sclerosing Cholangitis Risk Estimate Tool (PREsTo) Predicts Outcomes of the Disease: A Derivation and Validation Study Using Machine Learning.

Hepatology (Baltimore, Md.)
Improved methods are needed to risk stratify and predict outcomes in patients with primary sclerosing cholangitis (PSC). Therefore, we sought to derive and validate a prediction model and compare its performance to existing surrogate markers. The mod...

Predicting persistent depressive symptoms in older adults: A machine learning approach to personalised mental healthcare.

Journal of affective disorders
BACKGROUND: Depression causes significant physical and psychosocial morbidity. Predicting persistence of depressive symptoms could permit targeted prevention, and lessen the burden of depression. Machine learning is a rapidly expanding field, and suc...

Prediction and evaluation of the severity of acute respiratory distress syndrome following severe acute pancreatitis using an artificial neural network algorithm model.

HPB : the official journal of the International Hepato Pancreato Biliary Association
BACKGROUND: To predict the risk and severity of acute respiratory distress syndrome (ARDS) following severe acute pancreatitis (SAP) by artificial neural networks (ANNs) model.