Kraisangka J., Druzdzel M.J., Lohmueller L.C., Kanwar M.K., Antaki J.F., Benza R.L. (2019) Bayesian Network vs. Cox’s Proportional Hazard Model of PAH Risk: A Comparison. In: Riaño D., Wilk S., ten Teije A. (eds) Artificial Intelligence in Medicine. AIME 2019. Lecture Notes in Computer Science, vol 11526. Springer, Cham Abstract Pulmonary arterial hypertension (PAH) is […]
The Use of Risk Assessment Tools and Prognostic Scores in Managing Patients with Pulmonary Arterial Hypertension.
Kanwar M, Raina A, Lohmueller L, Kraisangka J, Benza R. Current Hypertension Reports. 2019 Apr 25;21(6):45. doi: 10.1007/s11906-019-0950-y. Review. PMID: 31025123 Abstract PURPOSE OF REVIEW: Pulmonary arterial hypertension (PAH) is a chronic, progressive, and incurable disease with significant morbidity and mortality. Despite increasingly available treatment options, PAH patients continue to experience disease progression and increased […]
ISHLT: Derivation of a Bayesian Network Model from an Existing Risk Score Calculator for Pulmonary Arterial Hypertension
Purpose: We propose an alternative approach to the extensively validated REVEAL risk score calculator using Bayesian network (BN) modeling. We derived a BN model with the same variables and discretization cut points as the REVEAL risk score calculator and data from the REVEAL registry. This study compared the performance and relative impact of the variables […]