AIMC Topic: Risk Assessment

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Application of electronic trigger tools to identify targets for improving diagnostic safety.

BMJ quality & safety
Progress in reducing diagnostic errors remains slow partly due to poorly defined methods to identify errors, high-risk situations, and adverse events. Electronic trigger (e-trigger) tools, which mine vast amounts of patient data to identify signals i...

Transforming Diabetes Care Through Artificial Intelligence: The Future Is Here.

Population health management
An estimated 425 million people globally have diabetes, accounting for 12% of the world's health expenditures, and yet 1 in 2 persons remain undiagnosed and untreated. Applications of artificial intelligence (AI) and cognitive computing offer promise...

Artificial neural network algorithm model as powerful tool to predict acute lung injury following to severe acute pancreatitis.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
OBJECTIVE: The aim of this study is to predict the risk of severe acute pancreatitis (SAP) associated with acute lung injury (ALI) by artificial neural networks (ANNs) model.

Recognition of Sedentary Behavior by Machine Learning Analysis of Wearable Sensors during Activities of Daily Living for Telemedical Assessment of Cardiovascular Risk.

Sensors (Basel, Switzerland)
With the recent advancement in wearable computing, sensor technologies, and data processing approaches, it is possible to develop smart clothing that integrates sensors into garments. The main objective of this study was to develop the method of auto...

Simulating exposure-related behaviors using agent-based models embedded with needs-based artificial intelligence.

Journal of exposure science & environmental epidemiology
Exposure to a chemical is a critical consideration in the assessment of risk, as it adds real-world context to toxicological information. Descriptions of where and how individuals spend their time are important for characterizing exposures to chemica...

Artificial intelligence: Implications for the health care risk manager?

Journal of healthcare risk management : the journal of the American Society for Healthcare Risk Management

Risk Evaluation Model of Highway Tunnel Portal Construction Based on BP Fuzzy Neural Network.

Computational intelligence and neuroscience
Risk assessment for tunnel portals in the construction stage has been widely recognized as one of the most critical phases in tunnel construction as it easily causes accident than the overall length of a tunnel. However, the risk in tunnel portal con...

Minimally invasive donor nephrectomy: current state of the art.

Langenbeck's archives of surgery
BACKGROUND: The concept of a minimally invasive live donor nephrectomy developed over 20 years ago. Surgeons gained expertise with the laparoscopic technique and utilized multiple variations that are now utilized in transplant centers throughout the ...

Calcium detection, its quantification, and grayscale morphology-based risk stratification using machine learning in multimodality big data coronary and carotid scans: A review.

Computers in biology and medicine
PURPOSE OF REVIEW: Atherosclerosis is the leading cause of cardiovascular disease (CVD) and stroke. Typically, atherosclerotic calcium is found during the mature stage of the atherosclerosis disease. It is therefore often a challenge to identify and ...

Using high-dimensional machine learning methods to estimate an anatomical risk factor for Alzheimer's disease across imaging databases.

NeuroImage
INTRODUCTION: The main goal of this work is to investigate the feasibility of estimating an anatomical index that can be used as an Alzheimer's disease (AD) risk factor in the Women's Health Initiative Magnetic Resonance Imaging Study (WHIMS-MRI) usi...