ArticleNPJ digital medicine2019
Precision medicine and the cursed dimensions.
Article in NPJ digital medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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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.
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Who cites it
8 citing papers in PubMed.
- Exploring the use of machine and deep learning in genome-wide association studies: a comprehensive review.BioData mining · 2026Review
- Radiographic phenotype-driven clustering in lumbar decompression: comparative study of outcome and reoperation risk.The spine journal : official journal of the North American Spine Society · 2026Article
- Enhancing chemotherapy response prediction via matched colorectal tumor-organoid gene expression analysis and network-based biomarker selection.Translational oncology · 2025Article
- Gdaphen, R pipeline to identify the most important qualitative and quantitative predictor variables from phenotypic data.BMC bioinformatics · 2023Article
- Article
- Hybrid modelling for stroke care: Review and suggestions of new approaches for risk assessment and simulation of scenarios.NeuroImage. Clinical · 2021Review
- Deep learning models in genomics; are we there yet?Computational and structural biotechnology journal · 2020Review
- Machine Learning to Detect Alzheimer's Disease from Circulating Non-coding RNAs.Genomics, proteomics & bioinformatics · 2019Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Our intuition regarding "average" is rooted in one-dimensional thinking, such as the distribution of height across a population. This intuition breaks down in higher dimensions when multiple measurements are combined: fewer individuals are close to average for many measurements simultaneously than for any single measurement alone. This phenomenon is known as the curse of dimensionality. In medicine, diagnostic sophistication generally increases through the addition of more predictive factors. Disease classes themselves become more dissimilar as a result, increasing the difficulty of incorporating (i.e., averaging) multiple patients into a single class for guiding treatment of new patients. Failure to consider the curse of dimensionality will ultimately lead to inherent limits on the degree to which precision medicine can extend the advances of evidence-based medicine for selecting suitable treatments. One strategy to compensate for the curse of dimensionality involves incorporating predictive observation models into the patient workup.
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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.