This dataset focuses on thyroid cancer recurrence after Radioactive Iodine (RAI) therapy. It contains 383 patient records with 13 key attributes, including age, gender, cancer staging, pathology type, risk classification, treatment response, and recurrence status. The data is valuable for predicting cancer recurrence, understanding risk factors, and evaluating treatment outcomes.

📊 Dataset Overview

📌 Total Rows: 383
📌 Total Columns: 13
📌 No Missing Values

🔹 Column Descriptions

• Age : Age of the patient (in years).
• Gender : Patient's gender (Male or Female).
• Hx Radiotherapy : History of prior radiotherapy (Yes or No).
• Adenopathy : Presence of lymph node involvement (Yes or No).
• Pathology : Type of thyroid cancer (e.g., Micropapillary).
• Focality : Tumor focality (Uni-Focal or Multi-Focal).
• Risk : Cancer risk classification (Low, Intermediate, High).
• T : Tumor classification (T1, T2, etc.).
• N : Lymph node classification (N0, N1, etc.).
• M : Metastasis classification (M0, M1, etc.).
• Stage : Cancer staging (Stage I, II, III, IV).
• Response : Treatment response (Excellent, Indeterminate, etc.).
• Recurred : Whether cancer recurred (Yes or No).

🔍 Key Questions to Explore

1️⃣ Are thyroid cancer recurrences more common in men or women?
2️⃣ How does age affect recurrence risk?
3️⃣ Can we predict recurrence based on tumor staging and pathology?
4️⃣ What is the relationship between treatment response and recurrence?

📂 Usage

This dataset is ideal for:
✅ Machine Learning Models for recurrence prediction
✅ Statistical Analysis of cancer progression
✅ Medical Research on thyroid cancer

🔗 Source

This dataset is a modified version of the original dataset:
Differentiated Thyroid Cancer Recurrence by Joe Beach Capital.
https://www.kaggle.com/datasets/joebeachcapital/differentiated-thyroid-cancer-recurrence
I have removed unnecessary columns to focus on thyroid cancer recurrence analysis.

📜 License

🔹 Attribution 4.0 International (CC BY 4.0) – You are free to use, share, and modify with proper credit.