Hepatitis C Prediction Dataset with Patient Demographics and Laboratory Values

Laboratory and demographic data for blood donors and Hepatitis C patients, sourced from the UCI Machine Learning Repository. The dataset includes patient age, sex, and 10 blood test results, with a target variable categorizing diagnosis from 'Blood Donor' to 'Cirrhosis'. Creators include researchers from the Medical University Hannover and the Helmholtz Centre for Infection Research.

Use Cases

• Classifying patient diagnosis categories based on demographic and laboratory data.
• Predicting Hepatitis C disease progression stages (Fibrosis, Cirrhosis) from blood test results.
• Analyzing the relationship between specific blood markers (e.g., ALB, ALT, AST) and liver disease states.

Strengths

• Includes a clear target variable for classification with five distinct diagnostic categories.
• Contains 14 attributes per patient, combining demographic data (Age, Sex) with 10 specific laboratory measurements.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

UCI Machine Learning Repository; original data from Institute of Clinical Chemistry, Medical University Hannover.

Collection Method

Clinical laboratory measurements from blood donors and patients.

Geography

Likely Germany, based on the institutions of the data donors.