ReviewNPJ systems biology and applications2026
In silico models in oncology, neurology, and epidemiology: systems-level and multiscale perspectives.
Review in NPJ systems biology and applications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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0 citing papers in PubMed.
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Authors and funding
5 authors.
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Abstract
Computational medicine uses mathematical modelling, high-performance computing, and the availability of large-scale biomedical data to study multiscale complex diseases. This review synthesises recent developments in in silico oncology, neurology, and epidemiology, highlighting their shared methodological foundations in systems theory and complex networks. We discuss how combining mechanistic approaches with machine learning integrates heterogeneous data. Finally, we identify translation barriers and outline future directions like digital twins for predictive, personalised healthcare.
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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 Socratic graph.