Cervical Cancer Patient Records (Synthetic)
Patient Health Records & Digital Health
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About
The Synthetic Cervical Cancer Patient Dataset is designed for educational and research purposes to analyze factors associated with cervical cancer, its progression, and diagnosis. The dataset includes anonymized, synthetic data on various clinical, behavioural, and laboratory factors for patients diagnosed with cervical cancer.
Dataset Features
- Age: Age of the patient (in years).
- Number of sexual partners: Total number of sexual partners the patient has had.
- First sexual intercourse: Age at first sexual intercourse.
- Number of pregnancies: Number of pregnancies the patient has had.
- Smokes: Whether the patient smokes (Yes/No).
- Smokes (years): Number of years the patient has been smoking.
- Smokes (packs/year): Number of packs of cigarettes the patient smokes per year.
- Hormonal Contraceptives: Whether the patient has used hormonal contraceptives (Yes/No).
- Hormonal Contraceptives (years): Number of years the patient has used hormonal contraceptives.
- IUD: Whether the patient has used an intrauterine device (Yes/No).
- IUD (years): Number of years the patient has used an intrauterine device.
- STDs: Whether the patient has been diagnosed with sexually transmitted diseases (Yes/No).
- STDs (number): The total number of sexually transmitted diseases the patient has been diagnosed with.
- STDs: condylomatosis: Whether the patient has been diagnosed with condylomatosis (Yes/No).
- STDs: cervical condylomatosis: Whether the patient has been diagnosed with cervical condylomatosis (Yes/No).
- STDs: vaginal condylomatosis: Whether the patient has been diagnosed with vaginal condylomatosis (Yes/No).
- STDs: vulvo-perineal condylomatosis: Whether the patient has been diagnosed with vulvo-perineal condylomatosis (Yes/No).
- STDs: syphilis: Whether the patient has been diagnosed with syphilis (Yes/No).
- STDs: pelvic inflammatory disease: Whether the patient has been diagnosed with pelvic inflammatory disease (Yes/No).
- STDs: genital herpes: Whether the patient has been diagnosed with genital herpes (Yes/No).
- STDs: molluscum contagiosum: Whether the patient has been diagnosed with molluscum contagiosum (Yes/No).
- STDs: AIDS: Whether the patient has been diagnosed with AIDS (Yes/No).
- STDs: HIV: Whether the patient has been diagnosed with HIV (Yes/No).
- STDs: Hepatitis B: Whether the patient has been diagnosed with Hepatitis B (Yes/No).
- STDs: HPV: Whether the patient has been diagnosed with Human Papillomavirus (Yes/No).
- STDs: Number of diagnosis: The total number of diagnoses for sexually transmitted diseases.
- STDs: Time since first diagnosis: Time in years since the patient was first diagnosed with an STD.
- STDs: Time since last diagnosis: Time in years since the patient's most recent STD diagnosis.
- Dx: Cancer: Whether the patient has been diagnosed with cancer (Yes/No).
- Dx: CIN: Whether the patient has been diagnosed with Cervical Intraepithelial Neoplasia (Yes/No).
- Dx: HPV: Whether the patient has been diagnosed with Human Papillomavirus (Yes/No).
- Dx: Diagnosis code (e.g., cancer, CIN).
- Hinselmann: Result from the Hinselmann test (Yes/No).
- Schiller: Result from the Schiller test (Yes/No).
- Citology: Cytology test result (Normal/Abnormal).
- Biopsy: Biopsy result (Normal/Abnormal).
Distribution


Usage
This dataset can be used for the following applications:
- Healthcare Analytics: Identify clinical and behavioral factors associated with cervical cancer progression and diagnosis.
- Predictive Modeling: Develop machine learning models to predict cervical cancer outcomes based on various factors.
- Clinical Research: Investigate the impact of sexual health, hormonal contraceptives, smoking, and STDs on cervical cancer risk.
- Educational Purposes: Provide a dataset for students in healthcare, medical, data science, and public health fields to analyze real-world clinical trends.
Coverage
This synthetic dataset is fully anonymized and complies with data privacy standards. It includes a variety of clinical and behavioral factors to support a broad range of research and analysis.
License
CC0 (Public Domain)
Who Can Use It
- Healthcare Researchers: To explore correlations between clinical, behavioral, and diagnostic factors and cervical cancer.
- Clinicians and Medical Practitioners: To analyze the impact of various risk factors on cervical cancer development.
- Data Scientists and Machine Learning Practitioners: To develop predictive models for cervical cancer diagnosis and prognosis.
- Educators and Students: As a resource for studying healthcare analytics and medical research.