» Articles » PMID: 2069131

Neural Network Analysis of Serial Cardiac Enzyme Data. A Clinical Application of Artificial Machine Intelligence

Overview
Specialty Pathology
Date 1991 Jul 1
PMID 2069131
Citations 8
Authors
Affiliations
Soon will be listed here.
Abstract

There has been a recent resurgence of interest in the study and application of computerized neural networks within the broad field of artificial intelligence. These "intelligent machines" are modeled after biological nervous systems and are fundamentally different from the many computerized expert systems that previously have been introduced as clinical decision-making aids. The authors describe a neural network designed and trained to predict the probability of acute myocardial infarction (AMI) based on the analysis of paired sets of cardiac enzymes. The neural network predicted 24 of 24 (100%) AMIs and 27 of 29 (93%) No-AMIs when compared with a pathologist's interpretation of the patient's laboratory data (P less than 0.000001). The authors attempted to validate the network's diagnoses by two independent methods. When compared with echocardiogram and EKG for diagnosis of AMI, the neural network agreed with the cardiologist's interpretation in 12 of 14 (86%) AMIs and 1 of 3 (33%) No-AMIs, but the correlation was not statistically significant. Using autopsy outcome for validation, the neural network agreed with the anatomic evidence in 24 of 26 (92%) AMIs and 4 of 6 (67%) No-AMIs (P = 0.001). The authors conclude that neural networks can be successfully applied to the analysis of cardiac enzyme data and suggest that broader applications exist within the domain of clinical decision support.

Citing Articles

The Evolution of Artificial Intelligence in Medical Imaging: From Computer Science to Machine and Deep Learning.

Avanzo M, Stancanello J, Pirrone G, Drigo A, Retico A Cancers (Basel). 2024; 16(21).

PMID: 39518140 PMC: 11545079. DOI: 10.3390/cancers16213702.


Machine learning for early prediction of acute myocardial infarction or death in acute chest pain patients using electrocardiogram and blood tests at presentation.

de Capretz P, Bjorkelund A, Bjork J, Ohlsson M, Mokhtari A, Nystrom A BMC Med Inform Decis Mak. 2023; 23(1):25.

PMID: 36732708 PMC: 9896766. DOI: 10.1186/s12911-023-02119-1.


Smart Diagnostics: Combining Artificial Intelligence and In Vitro Diagnostics.

McRae M, Rajsri K, Alcorn T, T McDevitt J Sensors (Basel). 2022; 22(17).

PMID: 36080827 PMC: 9459970. DOI: 10.3390/s22176355.


Cardiac ScoreCard: A Diagnostic Multivariate Index Assay System for Predicting a Spectrum of Cardiovascular Disease.

McRae M, Bozkurt B, Ballantyne C, Sanchez X, Christodoulides N, Simmons G Expert Syst Appl. 2019; 54:136-147.

PMID: 31467464 PMC: 6715313. DOI: 10.1016/j.eswa.2016.01.029.


Artificial intelligence to predict needs for urgent revascularization from 12-leads electrocardiography in emergency patients.

Goto S, Kimura M, Katsumata Y, Goto S, Kamatani T, Ichihara G PLoS One. 2019; 14(1):e0210103.

PMID: 30625197 PMC: 6326503. DOI: 10.1371/journal.pone.0210103.