Every treatment’s laboratory diagnostic and results are grouped. These records can be used in a retrospective analysis to look for a link between laboratory results and diseases and improve diagnosis efficiency and laboratory report quality. The study utilizes the J48 algorithm, a data mining technique, to predict abnormalities in 1,362 students’ peripheral blood smears. Researchers discovered that by employing four hematological characteristics (MCV, MCH, Hct, and RBC), the decision tree built by the algorithm can be used as a viable guideline for RBC morphology prediction. This will eventually lead to better test findings and more precise diagnoses.

Ten-fold cross-validation was used to evaluate the accuracy of all the classifiers. When compared to the RBC report, the accuracy, sensitivity, and specificity of the validation metrics were examined. The J48 algorithm for data mining demonstrates a distinct aspect of data mining in assessing a relationship of complicated data that exceeds the power of conventional statistics. This research demonstrates that laboratory data is critical in healthcare in many ways, including management, planning, and quality improvement. This is a well-written paper that should not be overlooked, especially by those studying concerning this field.

The Observation Report of Red Blood Cell Morphology in Thailand Teenager by Using Data Mining Technique – PMC

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3943190/

It is undeniable that laboratory information is important in healthcare in many ways such as management, planning, and quality improvement. Laboratory diagnosis and laboratory results from each patient are organized from every treatment. These data are …