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

Brief summary (registry, in English)

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.

What you commit to

• Study type: Observational
• Planned participants: 95
• From 13 Jul 2026 to the primary completion date, Dec 2027
• 1 site in 1 country
• Visits and tests: ask the trial team, the registry does not list them

Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.

Who cannot take part

Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.

Who the study is looking for

Age in the registry: 18 years to - · Sex: All · Does not accept healthy volunteers

Full criteria on ClinicalTrials.gov

Sites (1)

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