The Role of Artificial Intelligence for Providing Scientific Content for Laboratory Medicine

Author:

Wu Alan H B1,Jaffe Allan S2,Peacock William Franklin3,Kavsak Pete4,Greene Dina56ORCID,Christenson Robert H7

Affiliation:

1. Department of Laboratory Medicine, University of California, San Francisco , San Francisco, CA   United States

2. Departments of Cardiology and Laboratory Medicine, Mayo Clinic , Rochester, MN , United States

3. Department of Emergency Medicine, Baylor College of Medicine , Houston, TX , United States

4. Department of Pathology and Molecular Medicine, McMaster University , Hamilton, ON , Canada

5. Department of Laboratory Medicine, University of Washington , Seattle, WA , United States

6. LetsGetChecked Laboratories , Monrovia, CA , United States

7. Department of Pathology, University of Maryland , Baltimore, MD , United States

Abstract

Abstract Background Artificial intelligence (AI) promises to become an important tool in the practice of laboratory medicine. AI programs are available online that can provide concise medical and laboratory information within seconds after a question is submitted. Methods We posed the following contemporary and relevant question for clinical chemists using an AI program: “Should labs eliminate CK-MB testing?” The results of this inquiry were critically reviewed by a cardiologist, emergency department physician, and clinical laboratorians for accuracy and appropriateness. Results An AI report answering this question was generated within 15 s. The experts felt that the information was inaccurate with the statements that CK-MB results are released earlier than cardiac troponin (cTn), and are more useful for detection of myocardial injury in patients with renal insufficiencies. The summary omitted discussion on the ongoing debate for periprocedural detection of acute myocardial infarction (MI), the perceived value for detection of reinfarction, the value in risk stratification compared to cTn, the economic justification for testing both CK-MB and cTn, and medicolegal aspects of testing when results are discordant. Conclusions At this time, AI does not appear to be ready to be used by clinical laboratories for answering important practice questions.

Funder

BrainBox and Quidel

Roche Diagnostics

Siemens Healthineers

PixCell Medical

Abbott Diagnostics

Nexus

Ortho Clinical Diagnostics

Beckman Coulter, and Horiba

Publisher

Oxford University Press (OUP)

Subject

General Medicine

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