ReviewJournal of molecular biology2018
Patient Similarity Networks for Precision Medicine.
Review in Journal of molecular biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 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
55 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Visible neural networks for multi-omics integration: a critical review.Frontiers in artificial intelligence · 2025Pooled it
- Are risk factors necessary for pretest probability assessment of coronary artery disease? A patient similarity network analysis of the PROMISE trial.Journal of cardiovascular computed tomographyTrial
- Phenotyping Preeclampsia Using Unsupervised Machine Learning: A Prospective Cohort Study.BJOG : an international journal of obstetrics and gynaecology · 2026Article
- A Methodological Framework for Non-Invasive Body-Composition Phenotyping in Young Adults: Integrating Bioelectrical Impedance and Patient Similarity Networks.Life (Basel, Switzerland) · 2026Article
- Epigenetic biomarkers in inflammatory bowel diseases-computational challenges and opportunities.Journal of Crohn's & colitis · 2026Review
- Prediction Pipeline Selection for Incomplete Clinical Data via Missingness Fingerprints and Instance Augmentation.Bioengineering (Basel, Switzerland) · 2026Article
- Gene regulatory and biomolecular networks and their multifaceted biotechnological applications.World journal of microbiology & biotechnology · 2026Review
- Patient Similarity Networks for Irritable Bowel Syndrome: Revisiting Brain Morphometry and Cognitive Features.Diagnostics (Basel, Switzerland) · 2026Article
- Article
- Uncovering the Understanding of the Concept of Patient Similarity in Cancer Research and Treatment: Scoping Review.Journal of medical Internet research · 2025Article
- Deep learning-based computational approach for predicting ncRNAs-disease associations in metaplastic breast cancer diagnosis.BMC cancer · 2025Article
- miss-SNF: a multimodal patient similarity network integration approach to handle completely missing data sources.Bioinformatics (Oxford, England) · 2025Article
- Achieving clinically meaningful outcomes in digital health: a six-step, cyclical precision engagement framework (ENGAGE).Frontiers in digital health · 2025Article
- DeepMoIC: multi-omics data integration via deep graph convolutional networks for cancer subtype classification.BMC genomics · 2024Article
- Med-MGF: multi-level graph-based framework for handling medical data imbalance and representation.BMC medical informatics and decision making · 2024Article
- Elucidating Cancer Subtypes by Using the Relationship between DNA Methylation and Gene Expression.Genes · 2024Article
- StellarPath: Hierarchical-vertical multi-omics classifier synergizes stable markers and interpretable similarity networks for patient profiling.PLoS computational biology · 2024Article
- A Patient Similarity Network (CHDmap) to Predict Outcomes After Congenital Heart Surgery: Development and Validation Study.JMIR medical informatics · 2024Article
- Current and future directions in network biology.Bioinformatics advances · 2024Article
- Classifying breast cancer using multi-view graph neural network based on multi-omics data.Frontiers in genetics · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Clinical research and practice in the 21st century is poised to be transformed by analysis of computable electronic medical records and population-level genome-scale patient profiles. Genomic data capture genetic and environmental state, providing information on heterogeneity in disease and treatment outcome, but genomic-based clinical risk scores are limited. Achieving the goal of routine precision medicine that takes advantage of these rich genomics data will require computational methods that support heterogeneous data, have excellent predictive performance, and ideally, provide biologically interpretable results. Traditional machine-learning approaches excel at performance, but often have limited interpretability. Patient similarity networks are an emerging paradigm for precision medicine, in which patients are clustered or classified based on their similarities in various features, including genomic profiles. This strategy is analogous to standard medical diagnosis, has excellent performance, is interpretable, and can preserve patient privacy. We review new methods based on patient similarity networks, including Similarity Network Fusion for patient clustering and netDx for patient classification. While these methods are already useful, much work is required to improve their scalability for contemporary genetic cohorts, optimize parameters, and incorporate a wide range of genomics and clinical data. The coming 5 years will provide an opportunity to assess the utility of network-based algorithms for precision medicine.
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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.