ReviewNPJ digital medicine2024
Process mining in mHealth data analysis.
Review in NPJ digital medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Reciprocal Relationship Between Cardiovascular Risk and Attainment of Blood Pressure and Cholesterol Targets in Users of a Mobile Health App.High blood pressure & cardiovascular prevention : the official journal of the Italian Society of Hypertension · 2026Article
- An Integrated Predictive Impact-Enhanced Process Mining Framework for Strategic Oncology Workflow Optimization: Case Study in Iran.Bioengineering (Basel, Switzerland) · 2025Article
- Tinnitus Measured in Everyday Life: A Literature Review of Ecological Momentary Assessment Studies.Journal of the Association for Research in Otolaryngology : JARO · 2025Review
- Leveraging Kaizen with Process Mining in Healthcare Settings: A Conceptual Framework for Data-Driven Continuous Improvement.Healthcare (Basel, Switzerland) · 2025Article
- Healthcare trajectories of aging individuals during their last year of life: application of process mining methods to administrative health databases.BMC medical informatics and decision making · 2025Article
- Monitoring Colorectal Cancer Screening at Scale: Conformance Checking and Bottleneck Detection in Northern Portugal.Journal of primary care & community healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This perspective article explores how process mining can extract clinical insights from mobile health data and complement data-driven techniques like machine learning. Despite technological advances, challenges such as selection bias and the complex dynamics of health data require advanced approaches. Process mining focuses on analyzing temporal process patterns and provides complementary insights into health condition variability. The article highlights the potential of process mining for analyzing mHealth data and beyond.
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.