ArticleGenes2018
Artificial Intelligence and Integrated Genotype⁻Phenotype Identification.
Article in Genes, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed.
- Isolation and typing techniques for circulating tumor cells.Biomarker research · 2026Review
- Watermelon fruit metabolome gene discovery and its application in breeding: a review.Frontiers in plant science · 2025Review
- Physicians' Perspectives on AI in Clinical Decision Support Systems: Interview Study of the CURATE.AI Personalized Dose Optimization Platform.JMIR human factors · 2023Article
- Artificial intelligence in critical illness and its impact on patient care: a comprehensive review.Frontiers in medicine · 2023Review
- Recent Advances in Sugarcane Genomics, Physiology, and Phenomics for Superior Agronomic Traits.Frontiers in genetics · 2022Review
- Long non-coding RNAs and their potential impact on diagnosis, prognosis, and therapy in prostate cancer: racial, ethnic, and geographical considerations.Expert review of molecular diagnostics · 2021Review
- Review: Application of Artificial Intelligence in Phenomics.Sensors (Basel, Switzerland) · 2021Review
- Proteomic Profiling and Artificial Intelligence for Hepatocellular Carcinoma Translational Medicine.Biomedicines · 2021Review
- Artificial Intelligence and Digital Microscopy Applications in Diagnostic Hematopathology.Cancers · 2020Review
- Article
- Artificial Intelligence Pipeline to Bridge the Gap between Bench Researchers and Clinical Researchers in Precision Medicine.Med one · 2020Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
The integration of phenotypes and genotypes is at an unprecedented level and offers new opportunities to establish deep phenotypes. There are a number of challenges to overcome, specifically, accelerated growth of data, data silos, incompleteness, inaccuracies, and heterogeneity within and across data sources. This perspective report discusses artificial intelligence (AI) approaches that hold promise in addressing these challenges by automating computable phenotypes and integrating them with genotypes. Collaborations between biomedical and AI researchers will be highlighted in order to describe initial successes with an eye toward the future.
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.