Explainable AI for Predicting Hospital Admissions in Heart Failure: ExplAIn-HF

The goal of this observational study is to develop and validate an XAI based model that predicts HF events and identifies modifiable con-tributing factors, and to evaluate the added value of integrating high frequency smartwatch data compared to usual care in patients with heart failure. The main objectives of the study are: 1. To develop and validate an XAI based model that predicts HF events and identifies modifiable contributing factors, and to evaluate the added value of integrating high frequency smartwatch data compared to usual care. In the Netherlands usual care includes remote monitoring of heartrate, blood pressure, weight and symptoms. 2. To include insights of the smartwatch into activity patterns, impact on quality of life (KCCQ-12), and patient satisfaction with net promoter score (NPS). Participants will wear a smartwatch for six months and perform an I-lead ecg with the smartwatch weekly.

NCT Number	NCT07689760
Lead Sponsor	Medisch Spectrum Twente Collaborators: Saxion University of Applied Sciences, Deventer Ziekenhuis, University of Twente, Ziekenhuisgroep Twente
Conditions	Heart Failure
Enrollment	95 participants
Start Date	2026-07
Primary Completion	2027-12 (estimated)
Study Completion	2027-12 (estimated)
Updated on ClinicalTrials.gov	2026-08-03