Articles related to PREDICTION MODELING

A study presented at AAPA 2024 shows that AI, particularly a multilayer perceptron model, significantly improves the prediction of in-hospital cardiac arrest in emergency settings compared to the traditional Modified Early Warning Score.

A large-scale randomized controlled trial has identified significant prognostic factors for overall survival (OS) and cancer-specific survival (CSS) in localized prostate cancer, offering new insights into optimizing treatment strategies using surgery and radiotherapy.

The TRIPOD+AI guidelines mark a significant update in the standards for reporting prediction models, incorporating advancements in AI to support rigorous, transparent research in healthcare settings, facilitating better clinical decision-making tools.

This study introduces a pivotal model that aids physicians in making informed decisions regarding bone marrow sampling for MGUS patients, utilizing a comprehensive set of biomarkers to predict the progression to SMM or worse conditions with high accuracy.

The CXR CVD-Risk model stands at the forefront of integrating deep learning with radiography, offering a novel lens through which physicians can assess cardiovascular risk, especially in scenarios where conventional risk factors are not discernible.

Innovative research using AI has identified early, gender-specific risk factors for Alzheimer’s, offering new avenues for preventive care in at-risk populations. Understanding these indicators is crucial for healthcare professionals aiming to implement early intervention strategies.