ArticleFASEB bioAdvances2025
Holistic precision wellness: Paving the way for next-generation precision medicine (ngPM) with AI, biomedical informatics, and clinical medicine.
Article in FASEB bioAdvances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed.
- Precision medicine in low-income settings and small island developing states.Nature reviews. Endocrinology · 2026Review
- Effectiveness of Homoeopathic Treatments for Sleep Disorders in Children and Adolescents: A Systematic Review According to the Principles of Evidence-Based Medicine.Children (Basel, Switzerland) · 2025Review
- Cancer Biomarkers: Reflection on Recent Progress, Emerging Innovations, and the Clinical Horizon.Cancers · 2025Article
- Genomic and Structural Investigation of Mutations in Biotinidase (BTD) Gene Deficiency in Greater Middle Eastern Cohort: Insights from Molecular Dynamics Study.Biomedicines · 2025Article
- Holistic precision wellness: Paving the way for next-generation precision medicine (ngPM) with AI, biomedical informatics, and clinical medicine.FASEB bioAdvances · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A "quiet revolution" in medicine has been taking place over the past two decades. There are two converging dynamic forces that have propelled precision medicine to the limelight, garnering wide public attention. The first driver is the realization that populations within a disease area can be stratified, thus developing therapies tailored to their specific needs, and the capability to identify these populations by analyzing large, diverse datasets. The second driver is technology advances in multi-omics approaches and applications (i.e., molecularly informed medicine) enabling a more comprehensive portrait of disease biology. This promises to not only accelerate the development of precision medicine processes but also presents challenges for healthcare professionals and health systems that are struggling to interconnect and integrate disparate data sources into a cohesive clinical strategy to the benefit of their patients. We coin here the term next-generation precision medicine (ngPM), which is bound to become conventional in the clinics sooner or later. Artificial intelligence (AI) and machine learning (ML) in healthcare have transformative potential and are a strategic response to today's challenges and tomorrow's opportunities. The chief challenges here are how well precision medicine (PM) permeates primary care to become a standard of care and drive toward precision wellness or precision lifestyle (ngPM), while ensuring access to care is feasible, streamlined, and routine. We present here a perspective that would harness the power of ngPM for precision wellness.
Indexed as
Identifiers
What Socratic holds
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.