Articles related to PREDICTION MODELING

A multivariable screening test detects 90% of clinically significant prostate cancers vs 74% with PSA alone, suggesting PSA thresholds may miss aggressive disease despite similar false-positive rates.

The study found that novelty preference and task orientation in 7-month-olds were the strongest predictors of cognitive ability at age 30.

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.