Data mining, methodology, extracting hidden knowledge, breast cancer patient's, collecting data, storing data
Modern monitoring devices among other data collection devices have helped health care organization reduce their cost of collecting and storing data. Specialized tools that come with such equipment have made the entire data collection and storage process more effective thereby easing management's decision-making processes. Large medical data amounts exists in Jordan that require analysis to end up being useful.
[...] Most of these reported cases were from Amman, while most of the breast cancer patients were found to be non-smokers. Besides, most cases belonged to topographies and 504. On the other hand, the breast cancer patients' morphology was 8500. Again, the summery stage 3 was for clusters 1 and stage 5 for cluster 3 and then stage 7 for cluster 4. Mostly, alive patients were studied as opposed to deceased patients. Conclusions All that is contained in this study has presented some definitions of basic notions in the KDD field. [...]
[...] The Male Cancer Data Coordination with its trained health workers who are drawn from patient files then filed in the standard form are send straight to Jordan Cancer Registry where data is extracted including personal information as well as demographic information, diagnosis and tumor details. For the proposed method, statistical analysis is critical. In this case, the information about the tumor from specific examinations have to be gathered through staging techniques in order to establish the way the cancer is widespread. The information has to be combined through stage grouping to establish the stage of the disease. The disease could fall between stage 0 and stage IV. It would also be important to consider the aspects of knowledge discovery and data mining processes. [...]
[...] This was considered normal since 88% of the patients are non-smoker. Fig.7: Smoking status in cluster 0 In the case of the typology cluster was the greatest percentage for for 508, and for 504. Getting back to topology, it is easy to notice that and 504 are represented by and 10% respectively. This trend is critical in understanding why some areas are more infected as compared to others. The percentage of topology in cluster 0 is show in fig Fig.9: The percentage of topology in cluster 0 In the case of morphology, morph 8500 is found to have has the highest percentage of 80%. [...]
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