AIMC Topic: Laboratories, Clinical

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Identifying mislabelled samples: Machine learning models exceed human performance.

Annals of clinical biochemistry
BACKGROUND: It is difficult for clinical laboratories to identify samples that are labelled with the details of an incorrect patient. Many laboratories screen for these errors with delta checks, with final decision-making based on manual review of re...

Improving diagnosis in health care: laboratory medicine.

Diagnosis (Berlin, Germany)
Accurate and timely diagnosis remains one of the most complex and challenging processes in medicine. Diagnostic errors pose a significant burden on patients and healthcare systems, with laboratory-related errors playing a substantial role, especially...

Evaluation of error detection and treatment recommendations in nucleic acid test reports using ChatGPT models.

Clinical chemistry and laboratory medicine
OBJECTIVES: Accurate medical laboratory reports are essential for delivering high-quality healthcare. Recently, advanced artificial intelligence models, such as those in the ChatGPT series, have shown considerable promise in this domain. This study a...

General Applicability of Existing College of American Pathologists Accreditation Requirements to Clinical Implementation of Machine Learning-Based Methods in Molecular Oncology Testing.

Archives of pathology & laboratory medicine
CONTEXT.—: The College of American Pathologists (CAP) accreditation requirements for clinical laboratory testing help ensure laboratories implement and maintain systems and processes that are associated with quality. Machine learning (ML)-based model...

Regulation of artificial intelligence in healthcare: Clinical Laboratory Improvement Amendments (CLIA) as a model.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: To assess the potential to adapt an existing technology regulatory model, namely the Clinical Laboratory Improvement Amendments (CLIA), for clinical artificial intelligence (AI).

Validating, Implementing, and Monitoring Machine Learning Solutions in the Clinical Laboratory Safely and Effectively.

Clinical chemistry
BACKGROUND: Machine learning solutions offer tremendous promise for improving clinical and laboratory operations in pathology. Proof-of-concept descriptions of these approaches have become commonplace in laboratory medicine literature, but only a sca...