Artificial neural network approach in laboratory test reporting: Learning algorithms

American Journal of Clinical Pathology

Volumn 146, Issue 2, 2016, Pages 227-237

  Demirci, Ferhat ^a,b   Akan, Pinar ^b,c   Kume, Tuncay ^c   Sisman, Ali Riza ^c   Erbayraktar, Zubeyde ^c   Sevinc, Suleyman ^d  

^a Dr Suat Seren Chest Diseases and Thoracic Surgery Training Hospital   (Turkey)

^b Institute of Health Sciences   (Turkey)

^c Department of Biochemistry Faculty of Medicine ^*  (Turkey)

^d DOKUZ EYLUL UNIVERSITY   (Turkey)

Author keywords

Autoverification; Biochemistry; Clinical laboratory; Information systems; Machine learning; Neural networks (computer)

Indexed keywords

ALANINE AMINOTRANSFERASE; ALKALINE PHOSPHATASE; ASPARTATE AMINOTRANSFERASE; CALCIUM; CHLORIDE; CREATININE; GAMMA GLUTAMYLTRANSFERASE; GLUCOSE; MAGNESIUM; POTASSIUM; SODIUM; UREA; URIC ACID;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BLOOD BIOCHEMISTRY; CLINICAL LABORATORY; CLINICAL LABORATORY PERSONNEL; CRITICAL VALUE; DECISION TREE; DIAGNOSTIC ACCURACY; DIAGNOSTIC ERROR; EXPERIMENTAL MODEL; FALSE NEGATIVE RESULT; FALSE POSITIVE RESULT; FEMALE; HUMAN; LABORATORY INFORMATION SYSTEM; LABORATORY TEST; MAJOR CLINICAL STUDY; MALE; MEASUREMENT PRECISION; PATIENT SAFETY; PREDICTIVE VALUE; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; SEX RATIO; SOFTWARE; UNIVERSITY HOSPITAL; URINE BIOCHEMISTRY; VALIDITY; ALGORITHM; MACHINE LEARNING; METHODOLOGY;

ALGORITHMS; CLINICAL LABORATORY INFORMATION SYSTEMS; HUMANS; MACHINE LEARNING; NEURAL NETWORKS (COMPUTER); RESEARCH DESIGN; SOFTWARE;

EID: 85013696200     PISSN: 00029173     EISSN: 19437722     Source Type: Journal    
DOI: 10.1093/ajcp/aqw104     Document Type: Article

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