Others titles
- Risk Factors for Cervical Cancer
- Predication of Indicators of Cervical Cancer
- Diagnosis of Cervical Cancer
Keywords
- Cervical Cancer
- Cervical Cancer Symptoms
- Signs of Cervical Cancer
- Causes of Cervical Cancer
- Cervical Cancer Risk Factors
- Sexually Transmitted Diseases
- Acquired Immune Deficiency Syndrome
- Human Immunodeficiency Virus
- HIV/AIDS
- Human Papillomavirus
Cervical Cancer Screening
This dataset is composed of responses from 858 patients and 36 variables focusing on the prediction of indicators or diagnosis of cervical cancer. The dataset provides demographic information, habits, and historic medical records of the 858 patients from Hospital Universitario de Caracas in Caracas, Venezuela. A number of the patients did not answer some of the questions due to privacy concerns.
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Description
Despite the possibility of prevention with regular cytological screening, cervical cancer is one of the significant causes of mortality in low-income countries killing more than a quarter of a million cases per year. This is because resources are very limited and patients have poor adherence to routine screening due to lack of awareness. In addition, prediction of individual patient’s risk and best screening strategy during diagnosis has become a challenge with the existence of several diagnostic methods and physician’s subjective preferences, usually based on expertise and comfort. Hence, prediction of cervical cancer using automated methods or computed aided diagnosis (CAD) system would require data from each source – modality and expertise.
This study was conducted to create a predictive model of transfer learning (TL) from one source to another, such as modality to an expert, in order to accurately predict risk for cervical cancer and consequently diagnose cervical cancer among patients.
About this Dataset
Data Info
Date Created | 2017-03-03 |
---|---|
Last Modified | 2017-03-03 |
Version | 2017-03-03 |
Update Frequency |
Never |
Temporal Coverage |
2017 |
Spatial Coverage |
Caracas, Venezuela |
Source | John Snow Labs; UCI Machine Learning Repository; Universidad Central de Venezuela, Caracas, Venezuela; INESC TEC & FEUP, Porto, Portugal; |
Source License URL | |
Source License Requirements |
N/A |
Source Citation |
N/A |
Keywords | Cervical Cancer, Cervical Cancer Symptoms, Signs of Cervical Cancer, Causes of Cervical Cancer, Cervical Cancer Risk Factors, Sexually Transmitted Diseases, Acquired Immune Deficiency Syndrome, Human Immunodeficiency Virus, HIV/AIDS, Human Papillomavirus |
Other Titles | Risk Factors for Cervical Cancer, Predication of Indicators of Cervical Cancer, Diagnosis of Cervical Cancer |
Data Fields
Name | Description | Type | Constraints |
---|---|---|---|
Age_of_Respondents | A featured risk factor for cervical cancer, this represents the age of patients from Hospital Universitario de Caracas who responded to the questions on demographic information, habits, and historic medical records; some did not answer some questions due to privacy | integer | level : Ratio |
Number_of_Sexual_Partners | Number of sexual partners as a featured risk factor for cervical cancer | integer | level : Ratio |
First_Sexual_Intercourse | Age of first sexual intercourse as a featured risk factor for cervical cancer | integer | level : Ratio |
Number_of_Pregnancies | Number of pregnancies as a featured risk factor for cervical cancer | integer | level : Ratio |
Is_Smoking | Smoking as a featured risk factor for cervical cancer; answers whether patient is smoking or not | boolean | - |
Smoking_in_Years | Length of smoking in years as featured risk factor for cervical cancer | number | level : Ratio |
Smoking_in_Packs_per_Year | Number of cigarette packs consumed per year of smoking as a featured risk factor for cervical cancer | number | level : Ratio |
Is_On_Hormonal_Contraceptives | Use of hormonal contraceptive as a featured risk factor for cervical cancer; answers whether patient is on contraceptives or not | boolean | - |
Hormonal_Contraceptives_in_Years | Number of years on hormonal contraceptives as a featured risk factor for cervical cancer | number | level : Ratio |
Is_On_IUD | Use of intrauterine device (IUD) as a featured risk factor for cervical cancer; answers whether patient is on IUD | boolean | - |
IUD_in_Years | Number of years on IUD as a featured risk factor for cervical cancer | number | level : Ratio |
Is_Diagnosed_with_STDs | Patient diagnosis of STDs as a featured risk factor for cervical cancer; answers whether patient has been diagnosed with STD | boolean | - |
Number_of_Years_with_STDs | Number of years with STDs acquired as featured risk factor for cervical cancer | integer | level : Ratio |
Is_STD_Condylomatosis | If STD is categorized as condylomatosis | boolean | - |
Is_STD_Cervical_Condylomatosis | If STD is categorized as cervical condylomatosis | boolean | - |
Is_STD_Vaginal_Condylomatosis | If STD is categorized as vaginal condylomatosis | boolean | - |
Is_STD_Vulvoperineal_Condylomatosis | If STD is categorized as vulvoperineal condylomatosis | boolean | - |
Is_STD_Syphilis | If STD is categorized as syphilis | boolean | - |
Is_STD_Pelvic_Inflammatory_Disease | IIf STD is categorized as inflammatory disease | boolean | - |
Is_STD_Genital_Herpes | If STD is categorized as genital herpes | boolean | - |
Is_STD_Molluscum_Contagiosum | If STD is categorized as molluscum contagiosum | boolean | - |
Is_STD_AIDS | If STD is categorized as Acquired Immune Deficiency Syndrome (AIDS) | boolean | - |
Is_STD_HIV | If STD is categorized as Human Immunodeficiency Virus (HIV) | boolean | - |
Is_STD_Hepatitis_B | If STD is categorized as hepatitis B | boolean | - |
Is_STD_HPV | If STD is categorized as Human Papillomavirus (HPV) | boolean | - |
Number_of_STD_Diagnosis | Number of STDs diagnosed as a featured risk factor for cervical cancer | integer | level : Ratio |
Time_Since_First_STD_Diagnosis | Time since first STD diagnosis | integer | level : Ratio |
Time_Since_Last_STD_Diagnosis | Time since last STD diagnosis | integer | level : Ratio |
Is_Diagnosis_Cancer | If patient is diagnosed with cancer or no | boolean | - |
Is_Diagnosis_CIN | If patient is diagnosed with cervical intraepithelial neoplasia (CIN) or no | boolean | - |
Is_Diagnosis_HPV | If patient is diagnosed with human papillomavirus (HPV) or no | boolean | - |
Is_Diagnosed | If patient is diagnosed with | boolean | - |
Is_Screening_Hinselmann | If screening strategy used to predict the patient's risk of cervical cancer is colposcopy using acetic acid done | boolean | - |
Is_Screening_Schiller | If screening strategy used to predict the patient's risk of cervical cancer is colposcopy using Lugol iodine | boolean | - |
Is_Screening_Cytology | If screening used to predict the patient's risk of cervical cancer is Cytology | boolean | - |
Is_Screening_Biopsy | If screening used to predict the patient's risk of cervical cancer is Biopsy | boolean | - |
Data Preview
Age of Respondents | Number of Sexual Partners | First Sexual Intercourse | Number of Pregnancies | Is Smoking | Smoking in Years | Smoking in Packs per Year | Is On Hormonal Contraceptives | Hormonal Contraceptives in Years | Is On IUD | IUD in Years | Is Diagnosed with STDs | Number of Years with STDs | Is STD Condylomatosis | Is STD Cervical Condylomatosis | Is STD Vaginal Condylomatosis | Is STD Vulvoperineal Condylomatosis | Is STD Syphilis | Is STD Pelvic Inflammatory Disease | Is STD Genital Herpes | Is STD Molluscum Contagiosum | Is STD AIDS | Is STD HIV | Is STD Hepatitis B | Is STD HPV | Number of STD Diagnosis | Time Since First STD Diagnosis | Time Since Last STD Diagnosis | Is Diagnosis Cancer | Is Diagnosis CIN | Is Diagnosis HPV | Is Diagnosed | Is Screening Hinselmann | Is Screening Schiller | Is Screening Cytology | Is Screening Biopsy |
18 | 4 | 15.0 | 1.0 | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | ||||||||
15 | 1 | 14.0 | 1.0 | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | ||||||||
34 | 1 | 1.0 | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | |||||||||
52 | 5 | 16.0 | 4.0 | True | 37.0 | 37.0 | True | 3.0 | False | False | False | False | False | False | False | False | False | False | False | False | False | False | True | False | True | False | False | False | False | False | |||||
46 | 3 | 21.0 | 4.0 | False | True | 15.0 | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | |||||||
42 | 3 | 23.0 | 2.0 | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | ||||||||
51 | 3 | 17.0 | 6.0 | True | 34.0 | 3.4 | False | True | 7.0 | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | True | True | False | True | |||||
26 | 1 | 26.0 | 3.0 | False | True | 2.0 | True | 7.0 | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | ||||||
45 | 1 | 20.0 | 5.0 | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | True | False | True | True | False | False | False | False | ||||||||
44 | 3 | 15.0 | True | 1.27 | 2.8 | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False | False |