ReviewAging2025
Deep learning and generative artificial intelligence in aging research and healthy longevity medicine.
Review in Aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- The role of gut microbiome in aging-associated diseases: where do we stand now and how technology will transform the future.Gut microbes · 2026Review
- The long-lived immune system of centenarians.Nature reviews. Immunology · 2026Review
- DJ-1 in the Neuro-cutaneous Aging Axis: Unifying Pathways of Parkinson's Disease Neurodegeneration, Progression, and Redox-Based Therapeutic Strategies for Healthy Longevity.Molecular neurobiology · 2026Review
- Upskilling in Healthy Longevity Medicine and Its Association With Physicians' Implementation Intent and Self-Reported Clinical Confidence: Cross-Sectional Observational Study.JMIR medical education · 2026Observational
- Artificial Intelligence Applications in Gastric Cancer Surgery: Bridging Early Diagnosis and Responsible Precision Medicine.Journal of clinical medicine · 2026Review
- Statistical Methods in Aging Research: Improving Current Practices and Embracing Emerging Approaches.Annual review of statistics and its application · 2026Article
- Embracing the Digital Revolution: How Artificial Intelligence is Transforming Clinical Trials in Older Participants.Drugs & aging · 2026Review
- Translating Geroscience Into Clinical Longevity Dermatology: From Mechanisms of Aging to Skin-Centered Interventions.Journal of cosmetic dermatology · 2026Article
- Automated generation of personalized trajectories of aging phenotypes with DyViA-GAN.Frontiers in aging · 2026Article
- Delaying liver aging: Analysis of structural and functional alterations.World journal of gastroenterology · 2025Article
- Biomarker integration and biosensor technologies enabling AI-driven insights into biological aging.Frontiers in aging · 2025Review
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
No grant is acknowledged in the PubMed record.
Abstract
With the global population aging at an unprecedented rate, there is a need to extend healthy productive life span. This review examines how Deep Learning (DL) and Generative Artificial Intelligence (GenAI) are used in biomarker discovery, deep aging clock development, geroprotector identification and generation of dual-purpose therapeutics targeting aging and disease. The paper explores the emergence of multimodal, multitasking research systems highlighting promising future directions for GenAI in human and animal aging research, as well as clinical application in healthy longevity medicine.
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.