AIMC Topic: Risk Assessment

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Ultrasound-based deep learning radiomics nomogram for risk stratification of testicular masses: a two-center study.

Journal of cancer research and clinical oncology
OBJECTIVE: To develop an ultrasound-driven clinical deep learning radiomics (CDLR) model for stratifying the risk of testicular masses, aiming to guide individualized treatment and minimize unnecessary procedures.

Report of the First ONTOX Stakeholder Network Meeting: Digging Under the Surface of ONTOX Together With the Stakeholders.

Alternatives to laboratory animals : ATLA
The first Stakeholder Network Meeting of the EU Horizon 2020-funded ONTOX project was held on 13-14 March 2023, in Brussels, Belgium. The discussion centred around identifying specific challenges, barriers and drivers in relation to the implementatio...

Modeling of Machine Learning-Based Extreme Value Theory in Stock Investment Risk Prediction: A Systematic Literature Review.

Big data
The stock market is heavily influenced by global sentiment, which is full of uncertainty and is characterized by extreme values and linear and nonlinear variables. High-frequency data generally refer to data that are collected at a very fast rate bas...

Analyzing the influential factors of process safety culture by hybrid hidden content analysis and fuzzy DEMATEL.

Scientific reports
Due to the complex nature of safety culture and process industries, several factors influence process safety culture. This paper presents a novel framework that combines the hidden content analysis method with Decision Making Trial and Evaluation Lab...

Machine learning methods for developing a predictive model of the incidence of delirium in cardiac intensive care units.

Revista espanola de cardiologia (English ed.)
INTRODUCTION AND OBJECTIVES: Delirium, recognized as a crucial prognostic factor in the cardiac intensive care unit (CICU), has evolved in response to the changing demographics among critically ill cardiac patients. This study aimed to create a predi...

Exploring the Potential of Artificial Intelligence in Adolescent Suicide Prevention: Current Applications, Challenges, and Future Directions.

Psychiatry
ObjectiveThe global surge in adolescent suicide necessitates the development of innovative and efficacious preventive measures. Traditionally, various approaches have been used, but with limited success. However, with the rapid advancements in artifi...

Improved accuracy and efficiency of primary care fall risk screening of older adults using a machine learning approach.

Journal of the American Geriatrics Society
BACKGROUND: While many falls are preventable, they remain a leading cause of injury and death in older adults. Primary care clinics largely rely on screening questionnaires to identify people at risk of falls. Limitations of standard fall risk screen...

The probable future of toxicology - probabilistic risk assessment.

ALTEX
Both because of the shortcomings of existing risk assessment methodologies, as well as newly available tools to predict hazard and risk with machine learning approaches, there has been an emerging emphasis on probabilistic risk assessment. Increasing...

Advancing Cardiovascular Risk Assessment with Artificial Intelligence: Opportunities and Implications in North Carolina.

North Carolina medical journal
Cardiovascular disease mortality is increasing in North Carolina with persistent inequality by race, income, and location. Artificial intelligence (AI) can repurpose the widely available electrocardiogram (ECG) for enhanced assessment of cardiac dysf...

Fully automated artificial intelligence-based coronary CT angiography image processing: efficiency, diagnostic capability, and risk stratification.

European radiology
OBJECTIVES: To prospectively investigate whether fully automated artificial intelligence (FAAI)-based coronary CT angiography (CCTA) image processing is non-inferior to semi-automated mode in efficiency, diagnostic ability, and risk stratification of...