AIMC Topic: Risk Assessment

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Level of adrenomedullin in cases with adrenal defficiency and its relation to mortality in patients with sepsis.

Tuberkuloz ve toraks
INTRODUCTION: The aim of this study was to determine the prognostic value of adrenomedullin, after evaluation of adrenal function in sepsis patients. We also evaluated other prognostic factors such as APACHE II score, proBNP, and CRP and their predic...

Risk prediction for cardiovascular disease using ECG data in the China kadoorie biobank.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
We set out to use machine learning techniques to analyse ECG data to improve risk evaluation of cardiovascular disease in a very large cohort study of the Chinese population. We performed this investigation by (i) detecting "abnormality" using 3 one-...

Fall risk probability estimation based on supervised feature learning using public fall datasets.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Risk of falling is considered among major threats for elderly population and therefore started to play an important role in modern healthcare. With recent development of sensor technology, the number of studies dedicated to reliable fall detection sy...

Suicide Risk Assessment in Hospitals: An Expert System-Based Triage Tool.

The Journal of clinical psychiatry
BACKGROUND: The November 2010 Joint Commission Sentinel Event Alert on the prevention of suicides in medical/surgical units and the emergency department (ED) mandates screening every patient treated as an outpatient or admitted to the hospital for su...

Testing the Relative Performance of Data Adaptive Prediction Algorithms: A Generalized Test of Conditional Risk Differences.

The international journal of biostatistics
Comparing the relative fit of competing models can be used to address many different scientific questions. In classical statistics one can, if appropriate, use likelihood ratio tests and information based criterion, whereas clinical medicine has tend...

Multicenter Comparison of Machine Learning Methods and Conventional Regression for Predicting Clinical Deterioration on the Wards.

Critical care medicine
OBJECTIVE: Machine learning methods are flexible prediction algorithms that may be more accurate than conventional regression. We compared the accuracy of different techniques for detecting clinical deterioration on the wards in a large, multicenter ...

A Risk Based Neural Network Approach for Predictive Modeling of Blood Glucose Dynamics.

Studies in health technology and informatics
For type 1 diabetes patients, maintaining the blood glucose (BG) at normal values is a challenging task due to e.g. variable insulin reactions, diets, lifestyles, emotional conditions, etc. Hyperglycemic and hypoglycemic events can generate various c...

Validating FMEA output against incident learning data: A study in stereotactic body radiation therapy.

Medical physics
PURPOSE: Though failure mode and effects analysis (FMEA) is becoming more widely adopted for risk assessment in radiation therapy, to our knowledge, its output has never been validated against data on errors that actually occur. The objective of this...