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Thyroid Cancer Patient Risk Dataset
Patient Health Records & Digital Health
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About
This dataset focuses on differentiated thyroid cancer recurrence, providing 13 clinicopathologic features to help predict recurrence. It was collected over a 15-year period, with each patient monitored for at least a decade. The dataset was created as part of research in the field of AI and Medicine, aiming to support risk stratification for thyroid cancer patients.
Columns
The dataset contains 17 columns detailing various patient attributes and medical observations:
- Age: Patient's age, with values ranging from 15 to 82.
- Gender: Patient's gender (e.g., Female, Male).
- Smoking: Indicates if the patient smokes (True, False).
- Hx Smoking: Indicates a history of smoking (True, False).
- Hx Radiotherapy: Indicates a history of radiotherapy (True, False).
- Thyroid Function: Describes the patient's thyroid function (e.g., Euthyroid, Clinical Hyperthyroidism).
- Physical Examination: Details findings from physical examination (e.g., Multinodular goiter, Single nodular goiter-right).
- Adenopathy: Information regarding adenopathy (e.g., No, Right).
- Pathology: Describes the pathology of the cancer (e.g., Papillary, Micropapillary).
- Focality: Indicates if the cancer is Uni-Focal or Multi-Focal.
- Risk: Assessed risk level (e.g., Low, Intermediate).
- T: Tumour classification based on TNM staging (e.g., T2, T3a).
- N: Node classification based on TNM staging (e.g., N0, N1b).
- M: Metastasis classification based on TNM staging (e.g., M0, M1).
- Stage: Overall cancer stage (e.g., I, II).
- Response: Patient's response to treatment (e.g., Excellent, Structural Incomplete).
- Recurred: The target variable, indicating if cancer recurred (True, False).
Distribution
The dataset is typically provided as a CSV data file. It contains 383 individual records across its 17 columns, with no missing values reported for any field.
Usage
This dataset is ideal for:
- Developing and evaluating machine learning models for predicting thyroid cancer recurrence.
- Risk stratification of thyroid cancer patients.
- Research at the intersection of AI and Medicine.
Coverage
The data was collected over a 15-year duration, with each patient followed for at least 10 years. It includes clinicopathologic features of individual patients. No specific geographic coverage details were provided.
License
Attribution 4.0 International (CC BY 4.0)
Who Can Use It
This dataset is primarily intended for:
- Researchers and scientists in the fields of Artificial Intelligence, Machine Learning, and Medicine.
- Data analysts and modellers interested in predictive analytics for health outcomes and disease recurrence.
Dataset Name Suggestions
- Thyroid Cancer Recurrence Prediction Data
- Differentiated Thyroid Cancer Recurrence Study
- Clinicopathologic Thyroid Cancer Recurrence Dataset
- Thyroid Cancer Patient Risk Data
Attributes
Original Data Source: Thyroid Cancer Patient Risk Dataset
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