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Liver Cancer Post-Ablation Patient Outcomes
Patient Health Records & Digital Health
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About
Evaluating the clinical outcomes of Hepatocellular Carcinoma (HCC) patients treated with Radiofrequency Ablation (RFA) is essential for refining treatment protocols. This collection documents various variables from 111 patients with localised HCC who underwent this specific ablation procedure. It aims to support investigations into whether machine learning can accurately forecast favourable outcomes post-treatment by analysing clinical indicators and patient history.
Columns
- Age: Numerical value indicating the patient's age in years.
- Male_Female: Categorical identifier for the patient's gender.
- Smoking: Categorical indicator of the patient’s tobacco usage status.
- HTN: Categorical field representing whether the patient has hypertension (high blood pressure).
- DM: Categorical field indicating the presence or absence of diabetes mellitus.
- WBcs: Numerical count of the patient's white blood cells.
- HGB: Numerical value representing the patient's haemoglobin level.
- PLt: Numerical count of the patient's platelets.
- PT: Numerical value for prothrombin time, measuring blood clotting speed.
- Pc: Numerical value representing the prothrombin concentration.
Distribution
The data is provided in a single CSV file named
RFA Dataset.csv with a size of approximately 8.59 kB. It contains 111 valid records, with 100% validity and no missing or mismatched entries reported for the core demographic and clinical variables. The file includes 27 columns in total, providing a thorough overview of the research variables.Usage
This resource is ideal for developing binary classification models to predict patient outcomes following interventional oncology procedures. It is well-suited for benchmarking machine learning algorithms, such as XGBoost, in a clinical diagnostic context. Researchers can use the varied numerical and categorical attributes to identify which biomarkers are most predictive of post-RFA success.
Coverage
The scope of this data involves 111 individuals diagnosed with localised Hepatocellular Carcinoma who were treated with Radiofrequency Ablation. The demographic focus remains on patients eligible for localised ablation therapy, covering 24 specific clinical variables analyzed during the research project.
License
CC0: Public Domain
Who Can Use It
Medical researchers can leverage these records to investigate the potential of automated prognosis in oncology. Data scientists may utilise the categorical and numerical fields to practice feature selection and model validation for healthcare applications. Furthermore, clinicians interested in the efficacy of RFA can explore the correlations between patient history and successful treatment outcomes.
Dataset Name Suggestions
- Predicting Hepatocellular Carcinoma Outcomes Post-RFA
- HCC Treatment Outcome Machine Learning Dataset
- Radiofrequency Ablation Clinical Variables and Prognosis
- Liver Cancer Post-Ablation Patient Outcomes
- Hepatocellular Carcinoma RFA Clinical Registry
Attributes
Original Data Source: Liver Cancer Post-Ablation Patient Outcomes
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