Gallstone
About
The clinical dataset was collected from the Internal Medicine Outpatient Clinic of Ankara VM Medical Park Hospital and includes data from 319 individuals (June 2022–June 2023), 161 of whom were diagnosed with gallstone disease. It contains 38 features, including demographic, bioimpedance, and laboratory data, and was ethically approved by the Ankara City Hospital Ethics Committee (E2-23-4632). Demographic variables are age, sex, height, weight, and BMI. Bioimpedance data includes total, extracellular, and intracellular water, muscle and fat mass, protein, visceral fat area, and hepatic fat. Laboratory features are glucose, total cholesterol, HDL, LDL, triglycerides, AST, ALT, ALP, creatinine, GFR, CRP, hemoglobin, and vitamin D. The dataset is complete, with no missing values, and balanced in terms of disease status, eliminating the need for additional preprocessing. It provides a strong foundation for machine learning-based gallstone prediction using non-imaging features.
Subject Area
Computer Science
Instances
320
Features
37
Data Types
Tabular
Tasks
Classification
Feature Types
Continuous
Features
| Name | Role | Type | Units | Missing Values | Description |
|---|---|---|---|---|---|
| Gallstone Status | Target | Binary | - | No | |
| Age | Feature | Integer | - | No | |
| Gender | Feature | Categorical | - | No | |
| Comorbidity | Feature | Categorical | - | No | |
| Coronary Artery Disease (CAD) | Feature | Binary | - | No | |
| Hypothyroidism | Feature | Binary | - | No | |
| Hyperlipidemia | Feature | Binary | - | No | |
| Diabetes Mellitus (DM) | Feature | Binary | - | No | |
| Height | Feature | Integer | - | No | |
| Weight | Feature | Continuous | - | No | |
| Body Mass Index (BMI) | Feature | Continuous | - | No | |
| Total Body Water (TBW) | Feature | Continuous | - | No | |
| Extracellular Water (ECW) | Feature | Continuous | - | No | |
| Intracellular Water (ICW) | Feature | Continuous | - | No | |
| Extracellular Fluid/Total Body Water (ECF/TBW) | Feature | Continuous | - | No | |
| Total Body Fat Ratio (TBFR) | Feature | Continuous | % | No | |
| Lean Mass (LM) | Feature | Continuous | % | No | |
| Body Protein Content (Protein) | Feature | Continuous | % | No | |
| Visceral Fat Rating (VFR) | Feature | Integer | - | No | |
| Bone MassBone Mass (BM) | Feature | Continuous | - | No | |
| Muscle Mass (MM) | Feature | Continuous | - | No | |
| Obesity | Feature | Continuous | % | No | |
| Total Fat Content (TFC) | Feature | Continuous | - | No | |
| Visceral Fat Area (VFA) | Feature | Continuous | - | No | |
| Visceral Muscle Area (VMA) | Feature | Continuous | kg | No | |
| Hepatic Fat Accumulation (HFA) | Feature | Categorical | - | No | |
| Glucose | Feature | Continuous | - | No | |
| Total Cholesterol (TC) | Feature | Continuous | - | No | |
| Low Density Lipoprotein (LDL) | Feature | Continuous | - | No | |
| High Density Lipoprotein (HDL) | Feature | Continuous | - | No | |
| Triglyceride | Feature | Continuous | - | No | |
| Aspartat Aminotransferaz (AST) | Feature | Continuous | - | No | |
| Alanin Aminotransferaz (ALT) | Feature | Continuous | - | No | |
| Alkaline Phosphatase (ALP) | Feature | Continuous | - | No | |
| Creatinine | Feature | Continuous | - | No | |
| Glomerular Filtration Rate (GFR) | Feature | Continuous | - | No | |
| C-Reactive Protein (CRP) | Feature | Continuous | - | No | |
| Hemoglobin (HGB) | Feature | Continuous | - | No | |
| Vitamin D | Feature | Continuous | - | No |
Introductory Paper
Early prediction of gallstone disease with a machine learning-based method from bioimpedance and laboratory data
Irfan Esen, Hilal Arslan, Selin Aktürk Esen, Mervenur Gülşen, Nimet Kültekin, Oğuzhan Özdemir. 2024.
Medicine
Additional Metadata
Authors
Irfan Esen
Hilal Arslan
Selin Aktürk
Mervenur Gülşen
Nimet Kültekin
Oğuzhan Özdemir
Year Created
2024
License
CC BY 4.0