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Overview of HCC; Data Mining Discovery (Multi-Center Study) |
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PP: 69-72 |
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doi:10.18576/ab/020302
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Author(s) |
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Mohamed Younis,
Abdallah Nawara,
Elsayed A.Elgohary,
Mohammad M. Sallam,
Ali Ismael,
Abd Elrazek Abd Elrazek,
Hamdy Mahfouz,
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Abstract |
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| Background and Aim: Hepatocellular carcinoma is one of the most aggressive cancers that represent a global health problem. It is the fifth most common cancer and the second most common cause of cancer related- mortality worldwide. Hence we conducted the current study using high performance- data mining technology to obscure hidden knowledge would be helpful guide for better predication, follow up and best management.
Patients and Methods: Retrospectively, 130 Egyptian patients presented with HCC were followed clinically and their data were analysed using high performance technology of data mining intellectual machine learning of Raid I software program.
Results: Amazing results were obtained using Knowledge discovered by data (KDD) such as Serum Creatinine and Total Bilirubin should be the best laboratory indicators for HCC progression. AFP may increase not for the HCC itself but for progression cirrhosis. Furthermore HCC biology should be considered than multiplicity. Conclusion: HCC still a major medical concern in Egypt. Data mining programs would be very helpful in such an area of oncology and future medicine.
Abbreviations: AASLD: American Association for the Study of the Liver Diseases, AI: Artificial Intelligence, AFP: Alfa-feto- protein, CA: Computational analysis, DM: Data Mining, KDD: Knowledge discovered by data, ML: Machine Learning.
Conflict of interest: No |
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