Univariate logistic regression analysis of risk of developing advanced lesions at surveillance, according to molecular and clinical characteristics of patients at the baseline colonoscopy.
The promise of machine learning successfully exploiting digital phenotyping data to forecast mental states in psychiatric populations could greatly improve clinical practice. Previous research focused
The variables BMI, waist, systolic and diastolic blood pressure are all logged. Variable coding: Smoking, smoke exposure and employment–yes = 1, no = 0; TB and HIV–positive = 1, negative = 0; educatio
Means of parameter values (M) and their standard errors (SEM) for the parameters estimated from fits to individual patient data in Fig 2. 50 realizations of the model were used for these estimates of