A random forest machine-learning algorithm using age, baseline systolic blood pressure, and heart-rate parameters differentiated orthostatic hypotension from non-OH patients with 90.6% accuracy.
Observational (n=663)
No
Background and Purpose Many elderly patients are unable to actively stand up by themselves and have contraindications to performing the head-up tilt test (HUTT). We aimed to develop screening algorithms for diagnosing orthostatic hypotension (OH) before performing the HUTT.
Kim et al. (Wed,) conducted a observational in Orthostatic hypotension (n=663). Machine-learning algorithms (random forest) vs. Head-up tilt test (HUTT) was evaluated on Classification accuracy of random forest algorithm for differentiating orthostatic hypotension. A random forest machine-learning algorithm using age, baseline systolic blood pressure, and heart-rate parameters differentiated orthostatic hypotension from non-OH patients with 90.6% accuracy.