ReviewBioengineering & translational medicine2024
AI-organoid integrated systems for biomedical studies and applications.
Review in Bioengineering & translational medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 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
42 citing papers in PubMed, 56 citations in OpenAlex.
- Organoid Intelligent Morphomics: Decoding the organoid morphome through artificial intelligence from phenotypic quantification to mechanistic insight.Bioactive materials · 2027Review
- Artificial Intelligence-Powered Histopathology in Stem Cell Research: Bridging Morphology, Function, and Omics.Current issues in molecular biology · 2026Review
- From aging biology to cardiac biotechnology: emerging platforms for modeling cardiac aging.JCI insight · 2026Review
- Cardiac microphysiological systems in cardiovascular research: Construction paradigms, maturation trajectories, and translational frontiers.Bioengineering & translational medicine · 2026Review
- Harnessing human tumor organoids for cancer modeling and precision therapy.Protein & cell · 2026Review
- Animal models of spinal cord injury in neuro-urological research.Nature reviews. Urology · 2026Review
- Mesoscale maladaptation in disease organoids.Disease models & mechanisms · 2026Article
- Next-Generation Strategies for Neural Repair and Regeneration: Neural Organoid Transplantation in the CNS.Cell proliferation · 2026Review
- Organoids as next-generation models for investigating intracranial tumours.Molecular brain · 2026Review
- Engineering Human Retinal Organoids and Eye-on-a-Chip Models for Degenerative Eye Disease.ACS biomaterials science & engineering · 2026Review
- Stem Cell-Derived Organoids for Cancer Therapy: Precision Medicine and Drug Selection.International journal of molecular sciences · 2026Review
- Nutritional, Ethical and Ecological Aspects of Cultured Meat with Particular Emphasis on Functional Food Production: A Comprehensive Literature Review.Foods (Basel, Switzerland) · 2026Review
- Recent advances in microfluidics and bioelectronics for three-dimensional organoid interfaces.Biomicrofluidics · 2026Article
- Organoids in drug development: from predictive models to regulatory integration.Drug discovery today · 2026Review
- From organoid culture to manufacturing: technologies for reproducible and scalable organoid production.npj biomedical innovations · 2026Review
- Towards learning and memory risk assessment with human brain organoids: barriers and opportunities.Frontiers in toxicology · 2026Review
- Lung cancer organoids for functional precision oncology: from disease modeling to clinical decision support.Frontiers in oncology · 2026Review
- Biomaterials in organoid research: current state and future directions.Frontiers in bioengineering and biotechnology · 2026Review
- Patient-derived organoids in gastric cancer: bridging the tumor microenvironment to functional precision oncology.Frontiers in bioengineering and biotechnology · 2026Review
- Lightweight Deep Learning Model for Classification of Normal and Abnormal Vasculature in Organoid Images.Sensors (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
In this review, we explore the growing role of artificial intelligence (AI) in advancing the biomedical applications of human pluripotent stem cell (hPSC)-derived organoids. Stem cell-derived organoids, these miniature organ replicas, have become essential tools for disease modeling, drug discovery, and regenerative medicine. However, analyzing the vast and intricate datasets generated from these organoids can be inefficient and error-prone. AI techniques offer a promising solution to efficiently extract insights and make predictions from diverse data types generated from microscopy images, transcriptomics, metabolomics, and proteomics. This review offers a brief overview of organoid characterization and fundamental concepts in AI while focusing on a comprehensive exploration of AI applications in organoid-based disease modeling and drug evaluation. It provides insights into the future possibilities of AI in enhancing the quality control of organoid fabrication, label-free organoid recognition, and three-dimensional image reconstruction of complex organoid structures. This review presents the challenges and potential solutions in AI-organoid integration, focusing on the establishment of reliable AI model decision-making processes and the standardization of organoid research.
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.