ReviewMayo Clinic proceedings2025
Individualized Medicine in the Era of Artificial Intelligence.
Review in Mayo Clinic proceedings, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
The goal of individualized medicine is to provide a precise approach for the prevention, diagnosis, and treatment of disease, utilizing information about an individual's genomic, environmental, and lifestyle patterns. The rapid advancements in artificial intelligence (AI) have led to the application of sophisticated approaches including machine learning, generative AI, and large language models that could lead to discoveries and practice implementations aimed at improving clinical decision making and health care delivery through diverse applications. Nevertheless, the exact role of AI in supporting individualized medicine continues to evolve. In this position paper, we present our principles of applying AI to bolster the vision of the Mayo Clinic Center for Individualized Medicine. Leveraging the Center for Individualized Medicine's strategy on innovation and transformation as well as existing state-of-the-art operational architecture and capacity in handling large corpora of data (ie, multiomics, digital, multimodal data), we envision an AI-powered integration of such information toward an enterprise-wide adoption to serve the needs of individualized clinical practice of 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.