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One of the rich data fields is the biomedical realm. There are detailed biomedical records, ranging from clinical conditions to different types of biochemical data and imaging equipment outputs. However, the manual extraction and transformation of biomedical patterns into mechanically comprehensible information is a cumbersome challenge since the biomedical field includes broad, dynamic, and complex knowledge. The main focus of this study is to analyze some of the available data mining patterns for the classification of medical cases with the systematic literature review method. Its emphasis is on studying techniques that are commonly used for the prognosis, classification, prediction, and treatment-related to recurrent and significant diseases like cancer, hepatitis, and cardiac diseases. Data mining can enhance healthcare choices and patient survival time. The researchers of this study hope that this research provides information on the data mining classification algorithms used to study medical cases that are not even mentioned in this study. |
