Applications of Artificial Intelligence in Clinical Diagnostics : A review
Description
This article is an academic review examining current advancements and limitations in the application of artificial intelligence in clinical diagnostics, with emphasis on laboratory medicine and medical imaging.
Other
This article reviews the application of artificial intelligence in clinical diagnostics, focusing on its role in improving accuracy, efficiency, and decision-making in laboratory and medical imaging workflows. It discusses key AI technologies such as machine learning and deep learning and their use in hematology, microbiology, pathology, and radiology.
The paper also highlights current challenges including data quality, algorithmic bias, ethical considerations, and limitations in clinical implementation, particularly in resource-constrained healthcare settings. Future directions are explored with emphasis on the integration of AI into clinical data systems and personalized medicine.
This work is intended as a narrative review contributing to the understanding of emerging AI applications in healthcare diagnostics.
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Additional titles
- Alternative title
- transforming clinical diagnostics through artificial intelligence
References
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