ascopubs.org

A Comparison of Logistic Regression Against Machine Learning Algorithms for Gastric Cancer Risk Prediction Within Real-World Clinical Data Streams

We trained models using logistic regression (LR) and four commonly used ML algorithms to predict NCGC from age-/sex-matched controls in two EHR systems: Stanford University and the University of ...
Open Heart

Development and validation of a 10-year predictive model for cardiovascular and metabolic disease risk: insights from a large-scale health examination cohort

Objective To develop and validate a 10-year predictive model for cardiovascular and metabolic disease (CVMD) risk using comprehensive health examination data from nearly 37 701 individuals.Methods ...
News Medical

AI models show promise in predicting heart disease risks, but lack validation

In a recent review published in BMC Medicine, scientists evaluate artificial intelligence models (AI-Ms) that predict cardiovascular disease (CVD) risks in general and specific populations while also ...
Machine Design

Standardizing Computational Models: Verification, Validation and Uncertainty Quantification

Computational models and simulations have had an important role in engineering analysis since as far back as the 1960s. It is widely recognized that the use of modeling and simulation tools can make ...
Medscape

Structure-Activity Models of Oral Clearance, Cytotoxicity, and LD50: A Screen for Promising Anticancer Compounds

Rat LD50 values were taken from the Registry of Toxic Effects of Chemical Substances (RTECS) database [55] and cytotoxicity values were taken from the public National Cancer Institute (NCI) ...
JSTOR Daily

PACIC Instrument: disentangling dimensions using published validation models

Objective. To better understand the structure of the Patient Assessment of Chronic Illness Care (PACIC) instrument. More specifically to test all published validation models, using one single data set ...