ArticleBiochemia medica2024
Prediction interval: A powerful statistical tool for monitoring patients and analytical systems.
Article in Biochemia medica, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- Effectiveness of Simulation-Based Teaching Methods in Learning Obstetric Emergencies Among Healthcare Students: A Systematic Review and Meta-Analysis.Obstetrics and gynecology international · 2026Review
- The Future of Tumor Markers: Advancing Early Malignancy Detection Through Omics Technologies, Continuous Monitoring, and Personalized Reference Intervals.Biomolecules · 2025Review
- Clinical Bedside Benchmarking Test for Measuring the Total Hemoglobin Concentration.Healthcare (Basel, Switzerland) · 2025Article
- Introducing prediction intervals for sample means.Biochemia medica · 2024Review
- Diagnosis Based on Population Data versus Personalized Data: The Evolving Paradigm in Laboratory Medicine.Diagnostics (Basel, Switzerland) · 2024Review
- From sedentary individuals to highly trained athletes: A comprehensive cardiovascular magnetic resonance imaging study of cardiac volumetry, function, and strain.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic ResonanceArticle
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Authors and funding
1 author.
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Abstract
Monitoring is indispensable for assessing disease prognosis and evaluating the effectiveness of treatment strategies, both of which rely on serial measurements of patients' data. It also plays a critical role in maintaining the stability of analytical systems, which is achieved through serial measurements of quality control samples. Accurate monitoring can be achieved through data collection, following a strict preanalytical and analytical protocol, and the application of a suitable statistical method. In a stable process, future observations can be predicted based on historical data collected during periods when the process was deemed reliable. This can be evaluated using the statistical prediction interval. Statistically, prediction interval gives an
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Registered trials
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