AIMC Topic: Laboratories, Clinical

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Machine learning-based error detection in the clinical laboratory: a critical review.

Critical reviews in clinical laboratory sciences
Laboratory test results play a crucial role in the modern medical decision-making process. As such, errors in any phase of the testing process can have substantial clinical and operational impacts. While the development of increasingly robust quality...

New insights in preanalytical quality.

Clinical chemistry and laboratory medicine
The negative impact of preanalytical errors on the quality of laboratory testing is now universally recognized. Nonetheless, recent technological advancements and organizational transformations in healthcare - catalyzed by the still ongoing coronavir...

Digital metrology in laboratory medicine: a call for bringing order to chaos to facilitate precision diagnostics.

Clinical chemistry and laboratory medicine
Laboratory medicine is faced with rapid developments in data exchange, secondary use of data and artificial intelligence. Safe exchange of laboratory data requires a suitable terminology standard. NPU, LOINC and SNOMED CT are increasingly used for th...

Revolutionizing Laboratory Practices: Pioneering Trends in Total Laboratory Automation.

Annals of laboratory medicine
Total laboratory automation (TLA) is a transformative solution in clinical laboratories that addresses growing demands for operational efficiency, accuracy, and rapid turnaround times in patient care. TLA integrates advanced technologies across pre-a...

Proceedings of the Clinical Microbiology Open 2024: artificial intelligence applications in clinical microbiology.

Journal of clinical microbiology
The Clinical Microbiology Open (CMO) is a meeting sponsored by the American Society for Microbiology (ASM) in collaboration with its Corporate Council and Clinical and Public Health Microbiology representatives, which is held to discuss topics that a...

Revolutionizing clinical laboratories: The impact of artificial intelligence in diagnostics and patient care.

Diagnostic microbiology and infectious disease
INTRODUCTION: The integration of artificial intelligence (AI) is fundamentally transforming clinical laboratories, significantly improving diagnostic precision and operational effectiveness in the fields of pathology, microbiology, and biochemistry. ...

From errors to excellence: the pre-analytical journey to improved quality in diagnostics. A scoping review.

Clinical chemistry and laboratory medicine
This scoping review focuses on the evolution of pre-analytical errors (PAEs) in medical laboratories, a critical area with significant implications for patient care, healthcare costs, hospital length of stay, and operational efficiency. The Covidence...

Are we ready to integrate advanced artificial intelligence models in clinical laboratory?

Biochemia medica
The application of advanced artificial intelligence (AI) models and algorithms in clinical laboratories is a new inevitable stage of development of laboratory medicine, since in the future, diagnostic and prognostic panels specific to certain disease...

Advancing Laboratory Medicine Practice With Machine Learning: Swift yet Exact.

Annals of laboratory medicine
Machine learning (ML) is currently being widely studied and applied in data analysis and prediction in various fields, including laboratory medicine. To comprehensively evaluate the application of ML in laboratory medicine, we reviewed the literature...

Data flow in clinical laboratories: could metadata and peridata bridge the gap to new AI-based applications?

Clinical chemistry and laboratory medicine
In the last decades, clinical laboratories have significantly advanced their technological capabilities, through the use of interconnected systems and advanced software. Laboratory Information Systems (LIS), introduced in the 1970s, have transformed ...