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Machine learning in laboratory medicine: waiting for the flood?
Federico Cabitza1,2, Giuseppe Banfi2
1Dipartimento di Informatica, Sistemistica e Comunicazione, University of Milano-Bicocca, Edificio U14, Viale Sarca 336, 20126 Milan, Italy, Phone: +390264487888.
Clinical Chemistry and Laboratory Medicine
|October 23, 2017
Summary
Machine learning and artificial intelligence are emerging tools in laboratory medicine. These data analytics methods show promise for improving diagnostic and prognostic capabilities in pathology.
Area of Science:
- Laboratory medicine
- Data analytics
- Artificial intelligence
Background:
- Machine learning (ML) applications in laboratory medicine are rapidly evolving.
- Integrating data analytics and AI offers new potential for medical insights.
Purpose of the Study:
- To review current applications of ML in laboratory medicine.
- To highlight the diagnostic and prognostic potential of ML in this field.
Main Methods:
- Review of existing literature on ML methods in laboratory medicine.
- Analysis of AI and data analytics models applied to laboratory data.
Main Results:
- Current ML applications in laboratory medicine are still in their early stages.
- Significant potential exists for ML in diagnostics and prognostics.
Conclusions:
- Physician-scientists should explore ML for enhanced laboratory medicine support.
- Further attention to ML in pathology and laboratory medicine is warranted.
