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Peer-reviewedCC BY-NC-NDNpj health systems

An agentic framework for intelligent clinical laboratory medicine.

  • He S Yang1
  • Weishen Pan2
  • Melissa M Cushing3
  • Peter M Fleischut4
  • Fei Wang5
5 affiliations
  1. 1Department of Pathology and Laboratory and Laboratory Medicine. Weill Cornell Medicine, New York, NY, USA. [email protected].
  2. 2Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA.
  3. 3Department of Pathology and Laboratory and Laboratory Medicine. Weill Cornell Medicine, New York, NY, USA.
  4. 4NewYork-Presbyterian Hospital, New York, NY, USA.
  5. 5Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA. [email protected].
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Abstract

Clinical laboratory medicine is fundamental to healthcare yet remains an underrecognized frontier for artificial intelligence. We propose LabARIA, a human-supervised multi-agent framework that coordinates laboratory data, quality management, workflow optimization, and operational intelligence. By integrating specialized agents under transparent governance, LabARIA enables proactive laboratory management while preserving human oversight. Laboratory medicine offers a promising environment for developing, evaluating, and translating trustworthy agentic AI into healthcare delivery.

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Cite

BibTeXRIS
BibTeX
@article{yang2026agentic,
  title = {{An agentic framework for intelligent clinical laboratory medicine.}},
  author = {He S Yang and Weishen Pan and Melissa M Cushing and Peter M Fleischut and Fei Wang},
  journal = {Npj health systems},
  year = {2026},
  month = oct,
  doi = {10.1038/s44401-026-00163-3},
  url = {https://europepmc.org/article/MED/42957762},
  note = {CC BY-NC-ND},
}
RIS
TY  - JOUR
TI  - An agentic framework for intelligent clinical laboratory medicine.
AU  - He S Yang
AU  - Weishen Pan
AU  - Melissa M Cushing
AU  - Peter M Fleischut
AU  - Fei Wang
PY  - 2026
DA  - 2026/10/28
JO  - Npj health systems
DO  - 10.1038/s44401-026-00163-3
UR  - https://europepmc.org/article/MED/42957762
AB  - Clinical laboratory medicine is fundamental to healthcare yet remains an underrecognized frontier for artificial intelligence. We propose LabARIA, a human-supervised multi-agent framework that coordinates laboratory data, quality management, workflow optimization, and operational intelligence. By integrating specialized agents under transparent governance, LabARIA enables proactive laboratory management while preserving human oversight. Laboratory medicine offers a promising environment for developing, evaluating, and translating trustworthy agentic AI into healthcare delivery.
SN  - 3005-1959
ER  -