Bredt LC, Peres LAB. Artificial neural network for prediction of acute kidney injury after liver transplantation for cirrhosis and hepatocellular carcinoma. Artif Intell Cancer 2021; 2(5): 51-59 [DOI: 10.35713/aic.v2.i5.51]
Reader's ID:
04232460
Submitted on:
November 03, 2021, 04:09
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Reader Comments:
The article published in the journal titled Artificial neural network for prediction of acute kidney injury after liver transplantation for cirrhosis and hepatocellular carcinoma had higher scope in futuristic healthcare demands.
Further machine learning might help selecting diagnostic procedures with high predictive power and thereby contribute to the improvement of clinical guidelines.
Recurrent neural network (RNN), developed by the Google subsidiary company DeepMind, that uses clinical data to predict a time course of the probability that a patient will develop acute kidney failure also favoring the utility of similar scope of research. I congratulate the author for the best work.
Reply from the Editorial Office:
Thank you very much for your comments.
Author's Reply:
Replied on April 01, 2022, 00:24
I would like to thank you for the comments on my manuscript, I totally agree about the potential application of ANNs and contribution to the improvement of clinical guidelines due its high predictive power for selecting diagnostic procedures and accessing treatment response.