ArticleScience translational medicine2012
Computational medicine: translating models to clinical care.
Article in Science translational medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 95 papers, 1 of them a synthesis 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
95 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Personalized respiratory medicine: exploring the horizon, addressing the issues. Summary of a BRN-AJRCCM workshop held in Barcelona on June 12, 2014.American journal of respiratory and critical care medicine · 2015Pooled it
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- In silico models in oncology, neurology, and epidemiology: systems-level and multiscale perspectives.NPJ systems biology and applications · 2026Review
- Beyond the diagnostic threshold: paradigm shift in laboratory medicine from passive reaction to predictive capability.Frontiers in medicine · 2026Article
- Experimental Validation of Time-Explicit Ultrasound Propagation Models with Sound Diffusivity or Viscous Attenuation in Biological Tissues Using COMSOL Multiphysics.Bioengineering (Basel, Switzerland) · 2025Article
- Eight quick tips for biologically and medically informed machine learning.PLoS computational biology · 2025Article
- A genetic algorithm optimization framework for the characterization of hyper-viscoelastic materials: application to human articular cartilage.Royal Society open science · 2024Article
- Generative deep learning furthers the understanding of local distributions of fat and muscle on body shape and health using 3D surface scans.Communications medicine · 2024Article
- Up digital and personal: How heart digital twins can transform heart patient care.Heart rhythm · 2024Review
- Using the Non-Adoption, Abandonment, Scale-Up, Spread, and Sustainability (NASSS) Framework to Identify Barriers and Facilitators for the Implementation of Digital Twins in Cardiovascular Medicine.Sensors (Basel, Switzerland) · 2023Article
- Digital Twins in Healthcare and Their Applicability in Rhinology: A Narrative Review.Journal of rhinology : official journal of the Korean Rhinologic Society · 2023Review
- Design considerations for a hierarchical semantic compositional framework for medical natural language understanding.PloS one · 2023Article
- Physics-Informed Neural Networks for Brain Hemodynamic Predictions Using Medical Imaging.IEEE transactions on medical imaging · 2022Article
- A Computational Platform Integrating a Mechanistic Model of Crohn's Disease for Predicting Temporal Progression of Mucosal Damage and Healing.Advances in therapy · 2022Article
- Clinical Impact of Computational Heart Valve Models.Materials (Basel, Switzerland) · 2022Review
- Computational Medicine: Past, Present and Future.Chinese journal of integrative medicine · 2022Article
- MedGCN: Medication recommendation and lab test imputation via graph convolutional networks.Journal of biomedical informatics · 2022Article
- Evaluating the state of the art in missing data imputation for clinical data.Briefings in bioinformatics · 2022Article
- A general framework for quantifying uncertainty at scale.Communications engineering · 2022Article
- Mechanisms of arrhythmia termination during acute myocardial ischemia: Role of ephaptic coupling and complex geometry of border zone.PloS one · 2022Article
35 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
4 authors.
Funding
Abstract
Because of the inherent complexity of coupled nonlinear biological systems, the development of computational models is necessary for achieving a quantitative understanding of their structure and function in health and disease. Statistical learning is applied to high-dimensional biomolecular data to create models that describe relationships between molecules and networks. Multiscale modeling links networks to cells, organs, and organ systems. Computational approaches are used to characterize anatomic shape and its variations in health and disease. In each case, the purposes of modeling are to capture all that we know about disease and to develop improved therapies tailored to the needs of individuals. We discuss advances in computational medicine, with specific examples in the fields of cancer, diabetes, cardiology, and neurology. Advances in translating these computational methods to the clinic are described, as well as challenges in applying models for improving patient health.
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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.