Raw Hematological Dataset for Anemia Analysis and Classification

This dataset comprises 1004 raw hematological records collected from patients at Medical Centre Hospital, Chattogram, for use in anemia analysis and classification. Each row represents one anonymized patient sample, and the dataset contains nine variables: Gender, Age, HGB (Hemoglobin), RBC (Red Blood Cell Count), PCV/HCT (Packed Cell Volume/Hematocrit), MCV (Mean Corpuscular Volume), MCH (Mean Corpuscular Hemoglobin), MCHC (Mean Corpuscular Hemoglobin Concentration), and Decision_Class as the target label for anemia classification. The data are presented in their original, unprocessed form to preserve transparency and allow researchers to perform their own preprocessing, feature engineering, statistical analysis, and machine learning modeling. Because the dataset is openly structured and clinically relevant, it can support applications in anemia detection, supervised machine learning, deep learning development, biomedical data analysis, and educational research. All records are de-identified and contain no personally identifiable information, supporting ethical use and open-data dissemination. The dataset was validated by Hasanul Alam Shaikat, a biochemist, who reviewed and verified the clinical relevance and consistency of the hematological measurements and class annotations before release.