The future of precision medicine: towards a more predictive personalized medicine is a research paper published in Emerging Topics in Life Sciences (2020). On theSindex it has a DataRank of 1.8. It has been cited 64 times, with 63 citing works in its 1-hop citation network.
Precision medicine can be defined as personalized medicine enhanced by technology. In the past, medicine has, in some cases, been personalized. For example, some drugs are dosed on an individualized basis based on age, body-mass index, comorbidities and other clinical parameters. However, overall, medicine has largely followed the ‘one-size-fits-all' paradigm as exemplified in the treatment of essential hypertension or type 2 diabetes mellitus. What has changed in the past few years is that technologies such as high throughput sequencing, mass spectrometry, microfluidics, and imaging can help conduct a multitude of complex measurements on clinical samples. Aided by analytics, these technologies have been providing an increasingly detailed picture of molecular and cellular alterations underlying numerous diseases and have revealed tremendous variability between individuals and patients at the molecular and cellular level. These findings have motivated a more personalized or ‘precision' approach to medicine, in which molecular and cellular markers help tailor patient management to each individual. Here we provide an overview of the key factors driving adoption of precision medicine and highlight current research that may soon make precision medicine more predictive.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.626
From this paper's citation signal
Citation Network Contribution
1.2
From 41 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 34% comes from its base citations and 66% from the citation network (41 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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