LIVER CANCER DETECTION USING MACHINE LEARNING

Main Article Content

RAGHAVENDRA
M. VAHINI
N. DEEPTHI
N. SARIKA
P. ABHISRI

Abstract

In a human body function of the liver is important. Many persons are suffering from liver disease, but they don't know it. The identification of liver diseases in the early stage helps a patient get better treatment. If it is not diagnosed earlier, it may lead to various health issues. To solve these issues, physicians need to examine whether the patient has been affected by liver disease or not, based on the multiple parameters. In this paper, we classify the patients who have liver disease or not by using different machine learning algorithms by comparing the performance factors and predicting the better result. The liver dataset is retrieved from the Kaggle dataset.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Article Details

How to Cite
RAGHAVENDRA, VAHINI, M. ., DEEPTHI, N. ., SARIKA, N. ., & ABHISRI, P. . (2023). LIVER CANCER DETECTION USING MACHINE LEARNING. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 14(03), 1247–1251. Retrieved from https://turcomat.org/index.php/turkbilmat/article/view/14312
Section
Articles

References

Dr Sultan ,Mrs. SumaLatha, S.Kavya, Monitoring of Indian Agriculture using LPC2148, Parishodh

Journal, ISSN NO:2347-6648, Volume XI, Issue VIII, August/2022,pg 21-25.

K.Sumalatha , K.Akshaya , K.Neha , M.Bhanu Sri,V2v System Congestion Control Validation And

Performance Using Can Communication And Tracking Of Vehicle, DogoRangsang Research Journal,

Issn: 2347-7180, Vol-12 Issue-02 2022,Pg 27-42

K. Sumalatha, S. Vaishnavi, S. Keerthi Sree, S. Harshitha Reddy, MFCC-based Deep CNN Model for

Emotion Detection from Speech and Facial Expression, Journal of Interdisciplinary Cycle Research, ISSN

NO: 0022-1945, Volume XIV, Issue XI, November/2022, Pg 787-796.

N. Jaswitha1 , N. Lavanya 2 , M. Chaya Prasanna3 , Mrs.K.Sumalatha4, Iot Based Transformer Health

Monitoring System, International Journal For Recent Developments In Science & Technology , Issn:

-4575,Volume 06, Issue 11, Nov 2022,Pg 1-7

Yuki Wakida, Yoshito Mekada, Ichiro Ide "Development of hepatocyte cancer detection method from

dynamic Computed tomography images" 2004. https://www.researchgate.net/publication/310050 161.

Jinshan Tang , Qingling Sun , Jun Liu , Yongyan Cao. "An Adaptive Anisotropic Diffusion Filter for Noise

Reduction in MR Images" 2007. https://ieeexplore.ieee.org/abstract/document/43 03737.

Y. Masuda, A. H. Foruzan, T. Tateyama, Y. W. Chen, "Automatic liver tumor detection using EM/MPM

algorithm and shape information ", IEICE technical 2010. https://ieeexplore.ieee.org/document/5542834.

Häme Y, Pollari M. "Semi -automatic liver tumor segmentation with hidden Markov measure field model

and non-parametric distribution estimation. MedImage Anal" 2011

https://www.ncbi.nlm.nih.gov/pubmed/21742543.

Alireza Mazloumi Gavgani, Yesim Serinagaoglu Dogrusoz. "Noise reduction using anisotropic diffusion

filter in inverse electrocardiology" 2012. https://ieeexplore.ieee.org/document/6347341.

William J. Richbourg, Jianfei Liu, Jeremy M. Watt, VivekPamulapati,Shijun "Tumor Burden Analysis on

Computed Tomography byAutomated Liver and Tumor Segmentation,"IEEETRANSACTIONS ON

MEDICAL IMAGING, 2012https://www.ncbi.nlm.nih.gov/pmc/articles/P MC3924860/