AIMC Topic: Risk Assessment

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A study on ship collision conflict prediction in the Taiwan Strait using the EMD-based LSSVM method.

PloS one
Ship collision accidents are the primary threat to traffic safety in the sea. Collision accidents can cause casualties and environmental pollution. The collision risk is a major indicator for navigators and surveillance operators to judge the collisi...

Development and Validation of Machine Learning Models to Predict Admission From Emergency Department to Inpatient and Intensive Care Units.

Annals of emergency medicine
STUDY OBJECTIVE: This study aimed to develop and validate 2 machine learning models that use historical and current-visit patient data from electronic health records to predict the probability of patient admission to either an inpatient unit or ICU a...

Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records.

Nature protocols
Early prediction of patient outcomes is important for targeting preventive care. This protocol describes a practical workflow for developing deep-learning risk models that can predict various clinical and operational outcomes from structured electron...

Aiding clinical assessment of neonatal sepsis using hematological analyzer data with machine learning techniques.

International journal of laboratory hematology
INTRODUCTION: Early diagnosis and antibiotic administration are essential for reducing sepsis morbidity and mortality; however, diagnosis remains difficult due to complex pathogenesis and presentation. We created a machine learning model for bacteria...

Adverse Outcomes Prediction for Congenital Heart Surgery: A Machine Learning Approach.

World journal for pediatric & congenital heart surgery
OBJECTIVE: Risk assessment tools typically used in congenital heart surgery (CHS) assume that various possible risk factors interact in a linear and additive fashion, an assumption that may not reflect reality. Using artificial intelligence technique...

High-Efficiency Machine Learning Method for Identifying Foodborne Disease Outbreaks and Confounding Factors.

Foodborne pathogens and disease
The China National Center for Food Safety Risk Assessment (CFSA) uses the Foodborne Disease Monitoring and Reporting System (FDMRS) to monitor outbreaks of foodborne diseases across the country. However, there are problems of underreporting or errone...

Pre-existing and machine learning-based models for cardiovascular risk prediction.

Scientific reports
Predicting the risk of cardiovascular disease is the key to primary prevention. Machine learning has attracted attention in analyzing increasingly large, complex healthcare data. We assessed discrimination and calibration of pre-existing cardiovascul...