Predictive modelling in healthcare
Risk, prognosis, and forecasting models built and validated on real clinical data.
Published on 10 October 2026 as the second issue of the Journal of Predictive Health Analytics and Clinical Informatics (JPHACI). Two double-blind peer-reviewed articles define the journal's complementary directions. The first is a scoping review of clinically actionable artificial intelligence for early disease detection, mapping how multimodal laboratory biomarkers and point-of-care diagnostics perform in resource-limited settings and asking what separates analytical accuracy from clinical actionability. The second presents an intelligent computer-vision framework for eye-state detection and adaptive screen control, combining MediaPipe Face Mesh and eye-aspect-ratio analysis with automatic brightness adjustment and sleep management in a real-time Streamlit dashboard. The speciality of the issue is that it holds evidence synthesis and deployable systems together: one paper interrogates whether predictive models change clinical decisions, the other shows a predictive model running in real time on ordinary hardware.
JPHACI · Open-access · Peer-reviewed · Published monthly
JPHACI publishes scholarship on predictive modelling, clinical data science, and health informatics, with rigorous double-blind peer review and a scope-first editorial process designed to give authors candid, timely decisions.
Typical editorial timelines; actual times vary with submission volume and reviewer availability.
Risk, prognosis, and forecasting models built and validated on real clinical data.
Methods for messy, longitudinal, multi-modal patient data.
EHR data, standards, and pipelines that move evidence into care.
Validation, fairness, monitoring, and safe deployment at the point of care.
ISSN (Online): pending · CC BY 4.0 · OAI-PMH enabled · Editorial contact: [email protected]