ReviewJournal of general internal medicine2013
Bringing big data to personalized healthcare: a patient-centered framework.
Review in Journal of general internal medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers, 3 of them syntheses that pooled it.
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
87 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Barriers impeding research data sharing on chronic disease prevention among the older adults in low-and middle-income countries: a systematic review.Frontiers in public health · 2024Pooled it
- Global Trends in Research of Macrophages Associated With Acute Lung Injury Over Past 10 Years: A Bibliometric Analysis.Frontiers in immunology · 2021Pooled it
- A patient-level data meta-analysis of standard-of-care treatments from eight prostate cancer clinical trials.Scientific data · 2016Pooled it
- Public Reporting Systems in Health Care and the Underconceptualized Technical Substrate, a Core Information Systems Dimension: Scoping Review.JMIR medical informatics · 2026Article
- Global research trends in single-port robot-assisted radical prostatectomy: a visualization-based bibliometric analysis.Journal of robotic surgery · 2026Article
- User Character Strengths and Engagement Prediction on a Digital Mental Health Platform for Young People: Longitudinal Observational Study.Journal of medical Internet research · 2025Observational
- Autoencoder-Based Representation Learning for Similar Patients Retrieval From Electronic Health Records: Comparative Study.JMIR medical informatics · 2025Article
- Low birth weight risk prediction model: a prognostic study in the Birhan field site in Ethiopia.Journal of global health · 2025Article
- Interpretable machine learning models for the prediction of all-cause mortality and time to death in hemodialysis patients.Therapeutic apheresis and dialysis : official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy · 2025Article
- Evaluation of artificial intelligence robot's knowledge and reliability on dental implants and peri-implant phenotype.Scientific reports · 2025Article
- Evaluation and practical application of prompt-driven ChatGPTs for EMR generation.NPJ digital medicine · 2025Review
- Differences in changes of data completeness after the implementation of an electronic medical record in three surgical departments of a German hospital-a longitudinal comparative document analysis.BMC medical informatics and decision making · 2024Article
- The Use of Deep Learning and Machine Learning on Longitudinal Electronic Health Records for the Early Detection and Prevention of Diseases: Scoping Review.Journal of medical Internet research · 2024Article
- "R" you getting this? Factors contributing to the public's understanding, evaluation, and use of basic reproduction numbers for infectious diseases.BMC public health · 2024Article
- Effectiveness of DialBetesPlus, a self-management support system for diabetic kidney disease: Randomized controlled trial.NPJ digital medicine · 2024Article
- The Role of Artificial Intelligence in Identifying Depression and Anxiety: A Comprehensive Literature Review.Cureus · 2024Review
- Learning from vertically distributed data across multiple sites: An efficient privacy-preserving algorithm for Cox proportional hazards model with variable selection.Journal of biomedical informatics · 2024Article
- Fusion of Graph and Tabular Deep Learning Models for Predicting Chronic Kidney Disease.Diagnostics (Basel, Switzerland) · 2023Article
- Personalization strategies in digital mental health interventions: a systematic review and conceptual framework for depressive symptoms.Frontiers in digital health · 2023Review
- Article
27 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Faced with unsustainable costs and enormous amounts of under-utilized data, health care needs more efficient practices, research, and tools to harness the full benefits of personal health and healthcare-related data. Imagine visiting your physician's office with a list of concerns and questions. What if you could walk out the office with a personalized assessment of your health? What if you could have personalized disease management and wellness plan? These are the goals and vision of the work discussed in this paper. The timing is right for such a research direction--given the changes in health care, reimbursement, reform, meaningful use of electronic health care data, and patient-centered outcome mandate. We present the foundations of work that takes a Big Data driven approach towards personalized healthcare, and demonstrate its applicability to patient-centered outcomes, meaningful use, and reducing re-admission rates.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.