AIMC Topic: Risk Assessment

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Diagnostic Risk Prediction Models for Upper Gastrointestinal Cancers: A Systematic Review.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
Upper gastrointestinal (UGI) cancers are often detected late. Risk prediction models could facilitate earlier detection by identifying patients at risk for further investigation. We systematically reviewed evidence on UGI diagnostic risk prediction m...

Genetic Risk Scores in Stroke Research and Care.

Stroke
Stroke remains a leading cause of death and disability worldwide. While well-established risk factors play a major role, genetic predisposition is a crucial determinant of stroke susceptibility, with heritability estimates up to 39% for ischemic stro...

Evaluating the impact of artificial intelligence in antimicrobial stewardship: a comparative meta-analysis with traditional risk scoring systems.

Infectious diseases now
OBJECTIVES: The growing challenge of antimicrobial resistance (AMR) has underscored the urgent need for robust antimicrobial stewardship programs (AMS). Artificial intelligence (AI) and machine learning (ML) have emerged as promising tools to support...

Optimization of guidelines for Risk Of Recurrence/Prosigna testing using a machine learning model: a Swedish multicenter study.

Breast (Edinburgh, Scotland)
PURPOSE: Gene expression profiles are used for decision making in the adjuvant setting in hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer. While algorithms to optimize testing exist for RS/Oncotype Dx, no such efforts have focused ...

Machine learning for personalized risk assessment of HIV, syphilis, gonorrhoea and chlamydia: A systematic review and meta-analysis.

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
BACKGROUND: Machine learning (ML) shows promise for sexually transmitted infection (STI) risk prediction, but systematic evidence of its effectiveness remains fragmented.

Opposing-through crash risk forecasting using artificial intelligence-based video analytics for real-time application: integrating generalized extreme value theory and time series forecasting models.

Accident; analysis and prevention
Recent advancements in artificial intelligence (AI) and traffic sensing technologies provide significant opportunities for real-time crash risk forecasting. While forecasting based on historical crash data yields macroscopic insights into future cras...

Could vehicles analyze driving risks using human fuzzy semantic logic? A data-knowledge-driven new perspective.

Accident; analysis and prevention
Accurate risk identification is crucial for ensuring the safe operation of Host vehicles (HoVs) in environments shared with Neighboring vehicles (NeVs). Traditional risk identification mechanisms typically rely on large amounts of precise numerical d...

Collision risk prediction and takeover requirements assessment based on radar-video integrated sensors data: A system framework based on LLM.

Accident; analysis and prevention
There are safety risks when drivers take over the control of autonomous driving vehicles, and reducing unnecessary takeovers is essential to improve driving safety. This study seeks to develop an interpretable system framework for collision risk pred...

A framework for real-time traffic risk prediction incorporating cost-sensitive learning and dynamic thresholds.

Accident; analysis and prevention
In recent years, researchers have explored an innovative approach that leverages real vehicle trajectory data to simultaneously derive traffic state and risk level for real-time risk prediction, which is crucial for traffic safety. However, existing ...

Potential risks and hazards posed by the pressure of pharmaceuticals and personal care products on water treatment plants.

Environmental pollution (Barking, Essex : 1987)
Pharmaceuticals and personal care products (PPCPs) are widely used in various industrial and commercial products, contributing to their substantial presence in the environment. In recent years, numerous studies have focused on the environmental behav...