Evidence map›Paper›PMID 39527389›Full record

ReviewStem cell reviews and reports2025

Model Organoids: Integrated Frameworks for the Next Frontier of Healthcare Advancements.

Riya Bhattacharya, Debajyoti Bose, Tanveen Kaur, Rushik Patel, Oladri Renuka, Raul V Rodriguez

Abstract readReview
PubMed Publisher
In one paragraph

Review in Stem cell reviews and reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
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  5. Article
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Riya BhattacharyaAI-Research Centre, School of Business, Woxsen University, Hyderabad, Telangana, India.
Debajyoti BoseAI-Research Centre, School of Business, Woxsen University, Hyderabad, Telangana, India. debajyoti1024@gmail.com.ORCID 0000-0002-3457-6994
Tanveen KaurRoy J. Carver Department of Biochemistry, Biophysics, and Molecular Biology, Iowa State University of Science and Technology, Ames, IA, USA.
Rushik PatelAI-Research Centre, School of Business, Woxsen University, Hyderabad, Telangana, India.
Oladri RenukaAI-Research Centre, School of Business, Woxsen University, Hyderabad, Telangana, India.
Raul V RodriguezAI-Research Centre, School of Business, Woxsen University, Hyderabad, Telangana, India. raul.rodriguez@woxsen.edu.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The morphogenetic events leading to tissue formation can be recapitulated using organoids, which allows studying new diseases and modelling personalized medicines. In this review, culture systems comparable to human organs are presented, these organoids are created from pluripotent stem cells or adult stem cells. The efficient and reproducible models of human tissues are discussed for biobanking, precision medicine and basic research. Mechanisms used by these model systems with an overview of models from human cells are also covered. As human physiology is different from animals, culture conditions and tissue limits often become challenging. Organoids offer novel approaches for such cases with rapid screening, transplantation studies and in immunotherapy. Discrepancies with large datasets can be handled with an integrated framework of artificial intelligence or AI and machine learning. An attempt has been made to show the improved effectiveness, simplified iterations, along with image analysis that are possible from this synergy. AI-assisted organoids have the potential to transform healthcare by improving disease understanding and accelerating clinical decision-making through personalized and precision medicine.

Indexed as

Delivery of Health CareModels, BiologicalOrganoidsAnimalsArtificial IntelligenceHumansMachine LearningPluripotent Stem CellsPrecision MedicineArtificial intelligenceHuman tissuesMachine learningOrganoidsStem cells

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.