%0 Book Section
%A Maharlou, Hamidreza
%A Krause, Elischa
%A Müntefering, Fabian
%A Voges, Jan
%A Weihs, Antoine
%A Lucht, Michael
%A Grabe, Hans J.
%A Pollmann, Iris
%A Mueller, Franz-Josef
%A Weber, Heike
%A Oeltze-Jafra, Steffen
%Y Househ, Mowafa S.
%Y Tariq, Zain Ul Abideen
%Y Al-Zubaidi, Mahmood
%Y Shah, Uzair
%Y Huesing, Elaine
%T The P4D Dashboard: A Platform for Monitoring Clinical Studies
%C Amsterdam
%I IOS Press
%M DZNE-2025-00938
%B Studies in Health Technology and Informatics
%P 495 - 499
%D 2025
%< MEDINFO 2025 — Healthcare Smart × Medicine Deep / Househ, Mowafa S. (Editor) ; : IOS Press, , ; ISSN: 09269630=18798365 ; ISBN: 9781643686080 ; doi:10.3233/SHTI250889
%X The P4D (Personalized, Predictive, Precise </td><td width="150">
%X  Preventive Medicine for Major Depression) dashboard (https://p4dashboard.vercel.app) is a web-based platform for monitoring and generating data-driven insights within a multi-site clinical depression study. Part of the broader P4D initiative, which aims to advance personalized medicine for depression through deep phenotyping, genotyping, and machine learning, the dashboard addresses the challenge of integrating heterogeneous data sources. Dynamic visualizations and interactive filtering methods enable users to define and explore sub-cohorts, facilitating the understanding of complex patterns and tailoring data views to their specific needs. The dashboard also summarizes key metrics, allowing real-time monitoring of the data collection and the generation of actionable reports. The P4D dashboard has successfully identified data irregularities, such as missing followup assessments due to early patient discharge and site-specific recruitment disparities, enabling timely interventions to enhance data quality. With its adaptable and scalable framework, the dashboard may be applied to other clinical cohort studies in the future.
%K Humans
%K Precision Medicine: methods
%K User-Computer Interface
%K Depressive Disorder, Major: diagnosis
%K Depressive Disorder, Major: therapy
%K Machine Learning
%K Clinical monitoring (Other)
%K data integration (Other)
%K depression (Other)
%K dynamic visualization (Other)
%K interactive dashboard (Other)
%F PUB:(DE-HGF)7
%9 Contribution to a book
%R 10.3233/SHTI250889
%U https://pub.dzne.de/record/280260