Machine learning (ML) methods are proliferating in scientific research. However, the
adoption of these methods has been accompanied by failures of validity, reproducibility, and …

Precision medicine, utilizing genomic and phenotypic data, aims to tailor treatments for
individual patients. However, successful implementation into clinical practice is challenging …

The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual
Prognosis Or Diagnosis) statement was published in 2015 to provide the minimum reporting …

Artificial intelligence (AI) is often used to describe the automation of complex tasks that we
would attribute intelligence to. Machine learning (ML) is commonly understood as a set of …

Background Clinical prediction models are widely used in health and medical research. The
area under the receiver operating characteristic curve (AUC) is a frequently used estimate to …

Current and future healthcare professionals are generally not trained to cope with the
proliferation of artificial intelligence (AI) technology in healthcare. To design a curriculum …

Objectives To develop a framework to identify and evaluate spin practices and its facilitators
in studies on clinical prediction model regardless of the modeling technique. Study Design …

Machine learning (ML) methods are proliferating in scientific research. However, the
adoption of these methods has been accompanied by failures of validity, reproducibility, and …

Abstract Advances in Artificial Intelligence (AI) have led to AI systems' being used
increasingly in medical education research. Current methods of reporting on the research …

Introduction As complexity and comorbidities increase with age, the increasing number of
community-dwelling older adults poses a challenge to healthcare professionals in making …