39 citations · 56 across the 7 of their papers we have counts for
9 papers
Leveraging Cardiac Imaging to Improve ECG-Based Detection of Chagas Disease in Resource-Constrained Settings
Laura Alvarez-Florez, Daniel Uyterlinde, Samuel Ruipérez-Campillo +3
Chagas disease is a major cause of cardiomyopathy in Latin America. Cardiac magnetic resonance (CMR) imaging can characterize its structural abnormalities, but scanners and expert…
Embedding-Based Federated Learning with Runtime Governance for Iron Deficiency Prediction
Fan Zhang, Simon Deltadahl, Majid Lotfian Delouee +10
Recent reviews find that the vast majority of published healthcare federated learning (FL) studies never reach real-world deployment. We developed an embedding-based FL pipeline fo…
Enhancing Transparency and Traceability in Healthcare AI: The AI Product Passport
A. Anil Sinaci, Senan Postaci, Dogukan Cavdaroglu +6
Objective: To develop the AI Product Passport, a standards-based framework improving transparency, traceability, and compliance in healthcare AI via lifecycle-based documentation.…
Interpretable phenotyping of Heart Failure patients with Dutch discharge letters
Vittorio Torri, Machteld J. Boonstra, Marielle C. van de Veerdonk +6
Objective: Heart failure (HF) patients present with diverse phenotypes affecting treatment and prognosis. This study evaluates models for phenotyping HF patients based on left vent…
A Transformer-based survival model for prediction of all-cause mortality in heart failure patients: a multi-cohort study
Shishir Rao, Nouman Ahmed, Gholamreza Salimi-Khorshidi +8
We developed and validated TRisk, a Transformer-based AI model predicting 36-month mortality in heart failure patients by analysing temporal patient journeys from UK electronic hea…
Recent Methodological Advances in Federated Learning for Healthcare
Fan Zhang, Daniel Kreuter, Yichen Chen +10
For healthcare datasets, it is often not possible to combine data samples from multiple sites due to ethical, privacy or logistical concerns. Federated learning allows for the util…
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare
Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah +117
Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. I…
Real-time imputation of missing predictor values in clinical practice
Steven WJ Nijman, Jeroen Hoogland, T Katrien J Groenhof +6
Use of prediction models is widely recommended by clinical guidelines, but usually requires complete information on all predictors that is not always available in daily practice. W…
Multimodal Learning for Cardiovascular Risk Prediction using EHR Data
Ayoub Bagheri, T. Katrien J. Groenhof, Wouter B. Veldhuis +3
Electronic health records (EHRs) contain structured and unstructured data of significant clinical and research value. Various machine learning approaches have been developed to emp…