ArticlePhysiological genomics2018
Artificial intelligence, physiological genomics, and precision medicine.
Article in Physiological genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 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
31 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Convergence of disciplines: a systematic review of multidisciplinary development approaches in artificial intelligence.Frontiers in digital health · 2025Pooled it
- Molecular systems, human noncoding sequence variants, and blood pressure.Physiological reviews · 2026Review
- Critical success factors influencing business intelligence adoption: Evidence from Yemen.PloS one · 2026Article
- A Heart-to-Heart With ChatGPT: AI Applications in Hypertension.American journal of hypertension · 2025Review
- Ethics of artificial intelligence in prenatal and pediatric genomic medicine.Journal of community genetics · 2024Article
- Precision diagnostics in children.Cambridge prisms. Precision medicine · 2023Review
- Artificial Intelligence in Biological Sciences.Life (Basel, Switzerland) · 2022Review
- Article
- Artificial Intelligence in Cardiovascular Atherosclerosis Imaging.Journal of personalized medicine · 2022Review
- Genome-Wide Association Study Statistical Models: A Review.Methods in molecular biology (Clifton, N.J.) · 2022Review
- Applications of Artificial Intelligence in Myopia: Current and Future Directions.Frontiers in medicine · 2022Review
- Effect Evaluation of Artificial Intelligence-Based Electronic Health PDCA Nursing Model in the Treatment of Mycoplasma Pneumonia in Children.Journal of healthcare engineering · 2022Article
- Machine Learning, Deep Learning, and Closed Loop Devices-Anesthesia Delivery.Anesthesiology clinics · 2021Review
- Milestones of Precision Medicine: An Innovative, Multidisciplinary Overview.Molecular diagnosis & therapy · 2021Review
- Performance Comparisons of AlexNet and GoogLeNet in Cell Growth Inhibition IC50 Prediction.International journal of molecular sciences · 2021Article
- DNA-based screening and personal health: a points to consider statement for individuals and health-care providers from the American College of Medical Genetics and Genomics (ACMG).Genetics in medicine : official journal of the American College of Medical Genetics · 2021Article
- Artificial intelligence for good health: a scoping review of the ethics literature.BMC medical ethics · 2021Article
- Renal metabolism and hypertension.Nature communications · 2021Review
- Artificial Intelligence Enhances Studies on Inflammatory Bowel Disease.Frontiers in bioengineering and biotechnology · 2021Review
- Personalized medicine, digital technology and trust: a Kantian account.Medicine, health care, and philosophy · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Big data are a major driver in the development of precision medicine. Efficient analysis methods are needed to transform big data into clinically-actionable knowledge. To accomplish this, many researchers are turning toward machine learning (ML), an approach of artificial intelligence (AI) that utilizes modern algorithms to give computers the ability to learn. Much of the effort to advance ML for precision medicine has been focused on the development and implementation of algorithms and the generation of ever larger quantities of genomic sequence data and electronic health records. However, relevance and accuracy of the data are as important as quantity of data in the advancement of ML for precision medicine. For common diseases, physiological genomic readouts in disease-applicable tissues may be an effective surrogate to measure the effect of genetic and environmental factors and their interactions that underlie disease development and progression. Disease-applicable tissue may be difficult to obtain, but there are important exceptions such as kidney needle biopsy specimens. As AI continues to advance, new analytical approaches, including those that go beyond data correlation, need to be developed and ethical issues of AI need to be addressed. Physiological genomic readouts in disease-relevant tissues, combined with advanced AI, can be a powerful approach for precision medicine for common diseases.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.