Al-Azhar Assiut Medical Journal

EDITORIAL
Year
: 2016  |  Volume : 14  |  Issue : 1  |  Page : 7-

The future medicine


Abd E. M. Ali Hussein 
 Gastroenterology and Hepatology (Tropical Medicine), Faculty of Medicine, Al-Azhar University, Assiut, Egypt; Liver Transplant Department at UCLA, Los Angeles, California, USA

Correspondence Address:
Abd E. M. Ali Hussein
Visiting Assistant Project Scientist, Liver Surgery and Transplant, UCLA, USA




How to cite this article:
Ali Hussein AE. The future medicine.Al-Azhar Assiut Med J 2016;14:7-7


How to cite this URL:
Ali Hussein AE. The future medicine. Al-Azhar Assiut Med J [serial online] 2016 [cited 2020 Mar 31 ];14:7-7
Available from: http://www.azmj.eg.net/text.asp?2016/14/1/7/180463


Full Text

Several aspects of the management of patients with gastrointestinal and liver diseases have been investigated in the recent literature. Considering the peculiar pathophysiology of the disease progression or regression, multiple factors should be considered to reach the right diagnosis and correct management. Although our publications and scientific studies started in 2009 at the Kobe International Frontier Medical Center (KIFMC), Port Island, Japan for gastrointestinal, liver surgeries/endoscopy and liver transplant, here we present our experience in gastrointestinal tract, hepatology and liver transplantation using the novel computational analysis of data mining.

Analysing of our data by using data mining-computed program sheds light on the significant factors for each disease condition in the fields of hepatology and gastroenterology. Thus, the major challenge of biomedical data mining is to make these systems useful to biomedical researchers.

The decision tree analysis of all our publications in the American Journal of the Medical Sciences, USA; the European Journal of Gastroenterology and Hepatology, UK; Medicine, Baltimore, USA; and the Global Journal of Computer Sciences and Technology, USA was carried out using the Intelligent Miner software (Rapid Miner, Berlin, Germany). The best computational intelligent program of data mining software can automatically search a dataset to find the optimal classification variables, leading to the building of a decision tree algorithm. Briefly, all items derived from the patients were evaluated to determine which variables and cutoff points might produce the most dependent and independent factors for morbidity and mortality in each group or subgroup. Furthermore, the use of data mining can reform the overall quality of the present healthcare system [1],[2],[3],[4],[5],[6],[7],[8],[9].

Here, our group presented a manuscript stating that two-dimensional ultrasound can give predictive information regarding the treatment outcome before interferon therapy for hepatitis C virus-4 using data mining algorithms. Ultimately, such a study may give such a useful prediction before the therapy; furthermore, it would be repeated for the combination regimen of sofosbuvir/ribavirin with or without interferon therapy for those with hepatitis C virus G4; in addition, it can used for all new therapies.

I invite all readers to read the manuscript regarding the use of data mining technology, and also our previous publications. It is our belief that readers will come to know more about the new era of statistical computational analysis using data mining technology, and its advantages over the traditional mathematical analysis using Rapid I data mining.

References

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9Ali Hussein AE, Mahfouz H, Elazeem KA, Fakhry M, Elrazek EA, Foad M, et al, The Value of U/S to Determine Priority for Upper Gastrointestinal Endoscopy in Emergency Room. Medicine (Baltimore) 2015;94(49):e2241.