ReviewJournal of personalized medicine2022
Computational Models for Clinical Applications in Personalized Medicine-Guidelines and Recommendations for Data Integration and Model Validation.
Review in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 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
38 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Guidelines, Consensus Statements, and Standards for the Use of Artificial Intelligence in Medicine: Systematic Review.Journal of medical Internet research · 2023Pooled it
- [Development and validation of an interpretable machine learning model for predicting reguirement of early invasive mechanical ventilation in patients with acute pancreatitis].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2026Article
- On the usage of artificial intelligence for identifying main attributes and predicting neonatal sepsis.Scientific reports · 2026Article
- New Personalized Medicine Model for Medication Management.Journal of personalized medicine · 2026Review
- Hypothesis-driven approach to developmental toxicity assessment: Using mechanistic information to inform testing.Reproductive toxicology (Elmsford, N.Y.) · 2026Review
- Artificial Intelligence in Recurrent Pregnancy Loss: Current Evidence, Limitations, and Future Directions.Journal of clinical medicine · 2026Review
- Beyond the diagnostic threshold: paradigm shift in laboratory medicine from passive reaction to predictive capability.Frontiers in medicine · 2026Article
- Breast cancer risk prediction with a modified BOADICEA model in Danish women.British journal of cancer · 2026Article
- From diagnosis to dynamics: complex systems, transdiagnostics, and networks in forensic psychiatry.Frontiers in psychology · 2026Article
- Computational whole-body-exposome models for global precision brain health.Nature communications · 2025Article
- Modulating vascular stresses through homeostatic remodelling: a multi-patient analysis of atherosclerotic carotid biomechanics.Journal of the Royal Society, Interface · 2025Article
- Integrating Spatial Omics and Deep Learning: Toward Predictive Models of Cardiomyocyte Differentiation Efficiency.Bioengineering (Basel, Switzerland) · 2025Review
- ICOBA: A highly customizable iterative imagej macro for optimization of image co-localization batch analysis.SoftwareX · 2025Article
- The Potential Use of Digital Twin Technology for Advancing CAR-T Cell Therapy.Current issues in molecular biology · 2025Review
- Challenges and opportunities in uncertainty quantification for healthcare and biological systems.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Review
- Bridging the gap: From petri dish to patient - Advancements in translational drug discovery.Heliyon · 2025Review
- A computational cognitive neuroscience approach for characterizing individual differences in autism: Introduction to Special Issue.Personality neuroscience · 2025Article
- Proliferative Vitreoretinopathy in Retinal Detachment: Perspectives on Building a Digital Twin Model Using Nintedanib.International journal of molecular sciences · 2024Review
- Dose Individualisation of Antimicrobials from a Pharmacometric Standpoint: The Current Landscape.Drugs · 2024Review
- Network pharmacology and molecular docking: combined computational approaches to explore the antihypertensive potential of Fabaceae species.Bioresources and bioprocessing · 2024Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
The future development of personalized medicine depends on a vast exchange of data from different sources, as well as harmonized integrative analysis of large-scale clinical health and sample data. Computational-modelling approaches play a key role in the analysis of the underlying molecular processes and pathways that characterize human biology, but they also lead to a more profound understanding of the mechanisms and factors that drive diseases; hence, they allow personalized treatment strategies that are guided by central clinical questions. However, despite the growing popularity of computational-modelling approaches in different stakeholder communities, there are still many hurdles to overcome for their clinical routine implementation in the future. Especially the integration of heterogeneous data from multiple sources and types are challenging tasks that require clear guidelines that also have to comply with high ethical and legal standards. Here, we discuss the most relevant computational models for personalized medicine in detail that can be considered as best-practice guidelines for application in clinical care. We define specific challenges and provide applicable guidelines and recommendations for study design, data acquisition, and operation as well as for model validation and clinical translation and other research areas.
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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.