Analysis of laboratory biochemical results using AI aided model for Hepatocellular Carcinoma Diagnosis and Prediction
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Date
2023
Journal Title
Journal ISSN
Volume Title
Type
Other
Publisher
October university for modern sciences and arts
Series Info
Biochemistry Graduation Project 2022 - 2023;
Doi
Scientific Journal Rankings
Abstract
The aim of this study is to correlate between both Long noncoding RNAs (LncRNAs) and
hepatocellular carcinoma (HCC) with an attempt of integrating them in the diagnosis protocol for
HCC with the help of an artificial intelligence models. samples were collected and prepared by
third partner SHEFAA ALORMAN hospital. Then RNA was extracted using specific extraction
kits. Quantitative polymerase chain reaction (qPCR) was used later to determine specific RNA
concentration in previously prepared samples. Different models were created using different trial
of several data sets. The data sets were integrated into several algorithms, the non-AI traditional
results showed low accuracy but by integrating the artificial intelligence in the diagnosis it
enhanced the accuracy. The data was presented as mean ± SD where the results of LINC00853
were 29.92 ± 0.006711 with sensitivity and specificity of 97.14% and 95.71% respectively. The
results of HULC were 20.49 ± 11.29 with sensitivity 95.71% and specificity 94.29%. Firstly, a
model was built by using traditional data (ALT, AST, Total bilirubin and Serum albumin) and
showed a higher accuracy than traditional results. Secondly by the evaluation of the value of
addition of AFP to the previous parameters and it was d found that the accuracy increased when
compared to the model that was trained with the traditional data only. Finally, in order to increase
the accuracy of the data integration of novel LncRNAs (Highly up regulated in a liver cancer
(HULC)-long intergenic non protein coding 853(LINC00853)) was done where it showed
promising result. To conclude the novel LncRNAs biomarkers confirmed their potentiality as a
diagnostic tool for HCC diagnosis and their integration in AI model increased the sensitivity and
specificity for the diagnosis when compared to traditional data alone.
Description
Keywords
October University For Modern Sciences and Arts, MSA, جامعة أكتوبر للعلوم الحديثة والأداب, October University For Modern Sciences and Arts MSA, biochemistry, AI aided, Hepatocellular, Diagnosis
Citation
Faculty Of Pharmacy Graduation Project 2023 - 2024