AI Medical Compendium Topic:
Risk Assessment

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Equity in Using Artificial Intelligence Mortality Predictions to Target Goals of Care Documentation.

Journal of general internal medicine
BACKGROUND: Artificial intelligence (AI) algorithms are increasingly used to target patients with elevated mortality risk scores for goals-of-care (GOC) conversations.

How good are large language models at product risk assessment?

Risk analysis : an official publication of the Society for Risk Analysis
Product safety professionals must assess the risks to consumers associated with the foreseeable uses and misuses of products. In this study, we investigate the utility of generative artificial intelligence (AI), specifically large language models (LL...

Machine learning models' assessment: trust and performance.

Medical & biological engineering & computing
The common black box nature of machine learning models is an obstacle to their application in health care context. Their widespread application is limited by a significant "lack of trust." So, the main goal of this work is the development of an evalu...

Preface to the special issue of Food and Chemical Toxicology on "New approach methodologies and machine learning in food safety and chemical risk assessment: Development of reproducible, open-source, and user-friendly tools for exposure, toxicokinetic, and toxicity assessments in the 21st century".

Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association
This Special Issue contains articles on applications of various new approach methodologies (NAMs) in the field of toxicology and risk assessment. These NAMs include in vitro high-throughput screening, quantitative structure-activity relationship (QSA...

Re-evaluation of the prospective risk analysis for artificial-intelligence driven cone beam computed tomography-based online adaptive radiotherapy after one year of clinical experience.

Zeitschrift fur medizinische Physik
Cone-beam computed tomography (CBCT)-based online adaptation is increasingly being introduced into many clinics. Upon implementation of a new treatment technique, a prospective risk analysis is required and enhances workflow safety. We conducted a ri...

Precise risk-prediction model including arterial stiffness for new-onset atrial fibrillation using machine learning techniques.

Journal of clinical hypertension (Greenwich, Conn.)
Atrial fibrillation (AF) is the most common clinically significant cardiac arrhythmia and is an important risk factor for ischemic cerebrovascular events. This study used machine learning techniques to develop and validate a new risk prediction model...

Digital twins: reimagining the future of cardiovascular risk prediction and personalised care.

Hellenic journal of cardiology : HJC = Hellenike kardiologike epitheorese
The rapid evolution of highly adaptable and reusable artificial intelligence models facilitates the implementation of digital twinning and has the potential to redefine cardiovascular risk prevention. Digital twinning combines vast amounts of data fr...

Implementation of a Machine Learning Approach Evaluating Risk Factors for Complications after Single-Stage Augmentation Mastopexy.

Aesthetic plastic surgery
BACKGROUND: Single-stage mastopexy augmentation is a much-debated intervention due to its complexity and the associated relatively high complication rates. This study aimed to reevaluate the risk factors for these complications using a novel approach...

Dynamic and Transdiagnostic Risk Calculator Based on Natural Language Processing for the Prediction of Psychosis in Secondary Mental Health Care: Development and Internal-External Validation Cohort Study.

Biological psychiatry
BACKGROUND: Automatic transdiagnostic risk calculators can improve the detection of individuals at risk of psychosis. However, they rely on assessment at a single point in time and can be refined with dynamic modeling techniques that account for chan...

Assessing the risk of E. coli contamination from manure application in Chinese farmland by integrating machine learning and Phydrus.

Environmental pollution (Barking, Essex : 1987)
This study aims to present a comprehensive study on the risks associated with the residual presence and transport of Escherichia coli (E. coli) in soil following the application of livestock manure in Chinese farmlands by integrating machine learning...