ReviewFunctional & integrative genomics2024
The impact and future of artificial intelligence in medical genetics and molecular medicine: an ongoing revolution.
Review in Functional & integrative genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed.
- Therapeutic Potential of Somatostatin and Its Analogues in Alzheimer's Disease: From Molecular Mechanisms to Preclinical Studies.Molecular neurobiology · 2026Review
- Structural pharmacology of Chinese medicine: technological breakthroughs in decoding multi-target synergy and precision mechanisms.Advanced biotechnology · 2026Review
- AI-driven genotype-phenotype modeling: a framework integrating multi-modal single-cell genomics and reverse vaccinology forFrontiers in genetics · 2026Review
- Genomic innovations in cancer prevention, diagnosis, prognosis and precision therapeutics.Frontiers in genetics · 2026Review
- Advancing genome-based precision medicine: a review on machine learning applications for rare genetic disorders.Briefings in bioinformatics · 2025Review
- Population health management through human phenotype ontology with policy for ecosystem improvement.Frontiers in artificial intelligence · 2025Article
- The peculiar characteristics and advancement in diagnostic methodologies of influenza A virus.Frontiers in microbiology · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
46 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) platforms have emerged as pivotal tools in genetics and molecular medicine, as in many other fields. The growth in patient data, identification of new diseases and phenotypes, discovery of new intracellular pathways, availability of greater sets of omics data, and the need to continuously analyse them have led to the development of new AI platforms. AI continues to weave its way into the fabric of genetics with the potential to unlock new discoveries and enhance patient care. This technology is setting the stage for breakthroughs across various domains, including dysmorphology, rare hereditary diseases, cancers, clinical microbiomics, the investigation of zoonotic diseases, omics studies in all medical disciplines. AI's role in facilitating a deeper understanding of these areas heralds a new era of personalised medicine, where treatments and diagnoses are tailored to the individual's molecular features, offering a more precise approach to combating genetic or acquired disorders. The significance of these AI platforms is growing as they assist healthcare professionals in the diagnostic and treatment processes, marking a pivotal shift towards more informed, efficient, and effective medical practice. In this review, we will explore the range of AI tools available and show how they have become vital in various sectors of genomic research supporting clinical decisions.
Indexed as
Identifiers
39147901What 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.