TY - JOUR
T1 - Artificial intelligence in the pre-analytic phase - state-of-the-art and future perspectives
AU - Lippi, Giuseppe
AU - Mattiuzzi, Camilla
AU - Favaloro, Emmanuel J.
N1 - Publisher Copyright:
© 2024 Society of Medical Biochemists of Serbia. All rights reserved.
PY - 2024/1
Y1 - 2024/1
N2 - The use of artificial intelligence (AI) has become widespread in many areas of science and medicine, including laboratory medicine. Although it seems obvious that the analytical and post-analytical phases could be the most important fields of application in laboratory medicine, a kaleidoscope of new opportunities has emerged to extend the benefits of AI to many manual labor-intensive activities belonging to the pre-analytical phase, which are inherently characterized by enhanced vulnerability and higher risk of errors. These potential applications involve increasing the appropriateness of test prescription (with computerized physician order entry or demand management tools), improved specimen collection (using active patient recognition, automated specimen labeling, vein recognition and blood collection assistance, along with automated blood drawing), more efficient sample transportation (facilitated by the use of pneumatic transport systems or drones, and monitored with smart blood tubes or data loggers), systematic evaluation of sample quality (by measuring serum indices, fill volume or for detecting sample clotting), as well as error detection and analysis. Therefore, this opinion paper aims to discuss the state-of-the-art and some future possibilities of AI in the preanalytical phase.
AB - The use of artificial intelligence (AI) has become widespread in many areas of science and medicine, including laboratory medicine. Although it seems obvious that the analytical and post-analytical phases could be the most important fields of application in laboratory medicine, a kaleidoscope of new opportunities has emerged to extend the benefits of AI to many manual labor-intensive activities belonging to the pre-analytical phase, which are inherently characterized by enhanced vulnerability and higher risk of errors. These potential applications involve increasing the appropriateness of test prescription (with computerized physician order entry or demand management tools), improved specimen collection (using active patient recognition, automated specimen labeling, vein recognition and blood collection assistance, along with automated blood drawing), more efficient sample transportation (facilitated by the use of pneumatic transport systems or drones, and monitored with smart blood tubes or data loggers), systematic evaluation of sample quality (by measuring serum indices, fill volume or for detecting sample clotting), as well as error detection and analysis. Therefore, this opinion paper aims to discuss the state-of-the-art and some future possibilities of AI in the preanalytical phase.
KW - artificial intelligence
KW - errors
KW - preanalytical phase
KW - preanalytical variability
KW - robotics
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U2 - 10.5937/jomb0-45936
DO - 10.5937/jomb0-45936
M3 - Article
C2 - 38496022
AN - SCOPUS:85186763483
SN - 1452-8258
VL - 43
SP - 1
EP - 10
JO - Journal of Medical Biochemistry
JF - Journal of Medical Biochemistry
IS - 1
ER -