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

Kelwin Fernandes, Jaime S. Cardoso, and Jessica Fernandes. 'Transfer Learning with Partial Observability Applied to Cervical Cancer Screening.' Iberian Conference on Pattern Recognition and Image Analysis. Springer International Publishing, 2017.

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_RespondentsA 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 privacyintegerlevel : Ratio
Number_of_Sexual_PartnersNumber of sexual partners as a featured risk factor for cervical cancerintegerlevel : Ratio
First_Sexual_IntercourseAge of first sexual intercourse as a featured risk factor for cervical cancerintegerlevel : Ratio
Number_of_PregnanciesNumber of pregnancies as a featured risk factor for cervical cancerintegerlevel : Ratio
Is_SmokingSmoking as a featured risk factor for cervical cancer; answers whether patient is smoking or notboolean-
Smoking_in_YearsLength of smoking in years as featured risk factor for cervical cancernumberlevel : Ratio
Smoking_in_Packs_per_YearNumber of cigarette packs consumed per year of smoking as a featured risk factor for cervical cancernumberlevel : Ratio
Is_On_Hormonal_ContraceptivesUse of hormonal contraceptive as a featured risk factor for cervical cancer; answers whether patient is on contraceptives or notboolean-
Hormonal_Contraceptives_in_YearsNumber of years on hormonal contraceptives as a featured risk factor for cervical cancernumberlevel : Ratio
Is_On_IUDUse of intrauterine device (IUD) as a featured risk factor for cervical cancer; answers whether patient is on IUDboolean-
IUD_in_YearsNumber of years on IUD as a featured risk factor for cervical cancernumberlevel : Ratio
Is_Diagnosed_with_STDsPatient diagnosis of STDs as a featured risk factor for cervical cancer; answers whether patient has been diagnosed with STDboolean-
Number_of_Years_with_STDsNumber of years with STDs acquired as featured risk factor for cervical cancerintegerlevel : Ratio
Is_STD_CondylomatosisIf STD is categorized as condylomatosisboolean-
Is_STD_Cervical_CondylomatosisIf STD is categorized as cervical condylomatosisboolean-
Is_STD_Vaginal_CondylomatosisIf STD is categorized as vaginal condylomatosisboolean-
Is_STD_Vulvoperineal_CondylomatosisIf STD is categorized as vulvoperineal condylomatosisboolean-
Is_STD_SyphilisIf STD is categorized as syphilisboolean-
Is_STD_Pelvic_Inflammatory_DiseaseIIf STD is categorized as inflammatory diseaseboolean-
Is_STD_Genital_HerpesIf STD is categorized as genital herpesboolean-
Is_STD_Molluscum_ContagiosumIf STD is categorized as molluscum contagiosumboolean-
Is_STD_AIDSIf STD is categorized as Acquired Immune Deficiency Syndrome (AIDS)boolean-
Is_STD_HIVIf STD is categorized as Human Immunodeficiency Virus (HIV)boolean-
Is_STD_Hepatitis_BIf STD is categorized as hepatitis Bboolean-
Is_STD_HPVIf STD is categorized as Human Papillomavirus (HPV)boolean-
Number_of_STD_DiagnosisNumber of STDs diagnosed as a featured risk factor for cervical cancerintegerlevel : Ratio
Time_Since_First_STD_DiagnosisTime since first STD diagnosisintegerlevel : Ratio
Time_Since_Last_STD_DiagnosisTime since last STD diagnosisintegerlevel : Ratio
Is_Diagnosis_CancerIf patient is diagnosed with cancer or noboolean-
Is_Diagnosis_CINIf patient is diagnosed with cervical intraepithelial neoplasia (CIN) or noboolean-
Is_Diagnosis_HPVIf patient is diagnosed with human papillomavirus (HPV) or noboolean-
Is_DiagnosedIf patient is diagnosed withboolean-
Is_Screening_HinselmannIf screening strategy used to predict the patient's risk of cervical cancer is colposcopy using acetic acid doneboolean-
Is_Screening_SchillerIf screening strategy used to predict the patient's risk of cervical cancer is colposcopy using Lugol iodineboolean-
Is_Screening_CytologyIf screening used to predict the patient's risk of cervical cancer is Cytologyboolean-
Is_Screening_BiopsyIf screening used to predict the patient's risk of cervical cancer is Biopsyboolean-

Data Preview

Age_of_RespondentsNumber_of_Sexual_PartnersFirst_Sexual_IntercourseNumber_of_PregnanciesIs_SmokingSmoking_in_YearsSmoking_in_Packs_per_YearIs_On_Hormonal_ContraceptivesHormonal_Contraceptives_in_YearsIs_On_IUDIUD_in_YearsIs_Diagnosed_with_STDsNumber_of_Years_with_STDsIs_STD_CondylomatosisIs_STD_Cervical_CondylomatosisIs_STD_Vaginal_CondylomatosisIs_STD_Vulvoperineal_CondylomatosisIs_STD_SyphilisIs_STD_Pelvic_Inflammatory_DiseaseIs_STD_Genital_HerpesIs_STD_Molluscum_ContagiosumIs_STD_AIDSIs_STD_HIVIs_STD_Hepatitis_BIs_STD_HPVNumber_of_STD_DiagnosisTime_Since_First_STD_DiagnosisTime_Since_Last_STD_DiagnosisIs_Diagnosis_CancerIs_Diagnosis_CINIs_Diagnosis_HPVIs_DiagnosedIs_Screening_HinselmannIs_Screening_SchillerIs_Screening_CytologyIs_Screening_Biopsy
303163falsefalsefalsefalsefalsefalsefalsefalse
222171falsefalsefalsefalsefalsefalsefalsefalse
183161falsefalsefalsefalsefalsefalsefalsefalse
343falsefalsefalsefalsefalsefalsefalsefalsefalse
2317falsefalsefalsefalsefalsefalsefalsefalsefalse
262152falsefalsetruefalsetruefalsefalsefalsefalse
29192falsefalsefalsefalsefalsefalsefalsefalsefalse
25182falsefalsefalsefalsefalsefalsefalsefalsefalse
23192falsefalsefalsefalsefalsefalsefalsefalsefalse
17152falsefalsefalsefalsefalsefalsefalsefalsefalse