Machine Learning in Laboratory Medicine: Recommendations of the IFCC Working Group.

Saved in:
Bibliographic Details
Title: Machine Learning in Laboratory Medicine: Recommendations of the IFCC Working Group.
Authors: Master SR; Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, United States.; Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States., Badrick TC; Royal College of Pathologists of Australasia Quality Assurance Programs, Sydney, Australia., Bietenbeck A; MVZ Ärztliche Laboratorien München-Land GmbH, Poing, Germany., Haymond S; Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, United States.; Department of Pathology, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.
Source: Clinical chemistry [Clin Chem] 2023 Jul 05; Vol. 69 (7), pp. 690-698.
Publication Type: Journal Article; Research Support, N.I.H., Extramural
Journal Info: Publisher: Oxford University Press Country of Publication: England NLM ID: 9421549 Publication Model: Print Cited Medium: Internet ISSN: 1530-8561 (Electronic) Linking ISSN: 00099147 NLM ISO Abbreviation: Clin Chem Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1530-8561
DOI:10.1093/clinchem/hvad055