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Code for Intel & MobileODT Cervical Cancer Screening competition on Kaggle https://www.kaggle.com/c/intel-mobileodt-cervical-cancer-screening

Kaggle Intel & MobileODT Cervical Cancer Screening (4th place solution)

This repository contains clinical decision support (CDS) which provides recommendations for cervical cancer screening and management (CCSM).

A multistate dataset for colposcopy image classification of cervical cancer screening

Solution and summary for Intel & MobileODT Cervical Cancer Screening (3-class classification)

This repository contains the implementation of deep learning Convolutional Neural Network (CNN) algorithms for cervical cancer screening. The algorithm aims to assist in the early detection and classification of cervical cancer from digital cervical images.

Lesion segmentation for Cervical cancer screening using colposcopy images

Cervical type classification using convolutional neural nets

Repository for Kaggle's competition: "Intel and Mobile ODT Cervical Cancer Screening"

Machine Learning and Computer Vision methods for Cervical Cancer Screening

2nd place solution for Genentech Cervical Cancer Screening competition (www.kaggle.com)

No description available

Computer aided diagnosis for cervical cancer screening using image processing and machine learning

Keras implementation of kaggle image classification challenge (7th place)

Repo for https://www.kaggle.com/c/intel-mobileodt-cervical-cancer-screening

16th place solution for the Intel & MobileODT Cervical Cancer Screening competition on Kaggle

Cervical Cancer Screening and Surveillance CDSS

https://www.kaggle.com/c/cervical-cancer-screening

No description available

The microsimulation Markov model for cervical cancer screening (SiMCerC) was designed for cervical cancer screening in the Dutch context. The model can simulate a hypothetical population, including cervical cancer progression, and can apply various screening strategies to quantify their effects on the population. The model was coded in C++.

Cervical Cancer Risk Factors for Biopsy: This Dataset is Obtained from UCI Repository and kindly acknowledged! This file contains a List of Risk Factors for Cervical Cancer leading to a Biopsy Examination! About 11,000 new cases of invasive cervical cancer are diagnosed each year in the U.S. However, the number of new cervical cancer cases has been declining steadily over the past decades. Although it is the most preventable type of cancer, each year cervical cancer kills about 4,000 women in the U.S. and about 300,000 women worldwide. In the United States, cervical cancer mortality rates plunged by 74% from 1955 - 1992 thanks to increased screening and early detection with the Pap test. AGE Fifty percent of cervical cancer diagnoses occur in women ages 35 - 54, and about 20% occur in women over 65 years of age. The median age of diagnosis is 48 years. About 15% of women develop cervical cancer between the ages of 20 - 30. Cervical cancer is extremely rare in women younger than age 20. However, many young women become infected with multiple types of human papilloma virus, which then can increase their risk of getting cervical cancer in the future. Young women with early abnormal changes who do not have regular examinations are at high risk for localized cancer by the time they are age 40, and for invasive cancer by age 50. SOCIOECONOMIC AND ETHNIC FACTORS Although the rate of cervical cancer has declined among both Caucasian and African-American women over the past decades, it remains much more prevalent in African-Americans -- whose death rates are twice as high as Caucasian women. Hispanic American women have more than twice the risk of invasive cervical cancer as Caucasian women, also due to a lower rate of screening. These differences, however, are almost certainly due to social and economic differences. Numerous studies report that high poverty levels are linked with low screening rates. In addition, lack of health insurance, limited transportation, and language difficulties hinder a poor woman’s access to screening services. HIGH SEXUAL ACTIVITY Human papilloma viru

Cancer is a group of diseases involving abnormal cell growth with the potential to invade or spread to other parts of the body.[2][8] These contrast with benign tumors, which do not spread.[8] Possible signs and symptoms include a lump, abnormal bleeding, prolonged cough, unexplained weight loss, and a change in bowel movements.[1] While these symptoms may indicate cancer, they can also have other causes.[1] Over 100 types of cancers affect humans.[8] Tobacco use is the cause of about 22% of cancer deaths.[2] Another 10% are due to obesity, poor diet, lack of physical activity or excessive drinking of alcohol.[2][9][10] Other factors include certain infections, exposure to ionizing radiation, and environmental pollutants.[3] In the developing world, 15% of cancers are due to infections such as Helicobacter pylori, hepatitis B, hepatitis C, human papillomavirus infection, Epstein–Barr virus and human immunodeficiency virus (HIV).[2] These factors act, at least partly, by changing the genes of a cell.[11] Typically, many genetic changes are required before cancer develops.[11] Approximately 5–10% of cancers are due to inherited genetic defects.[12] Cancer can be detected by certain signs and symptoms or screening tests.[2] It is then typically further investigated by medical imaging and confirmed by biopsy.[13] The risk of developing certain cancers can be reduced by not smoking, maintaining a healthy weight, limiting alcohol intake, eating plenty of vegetables, fruits, and whole grains, vaccination against certain infectious diseases, limiting consumption of processed meat and red meat, and limiting exposure to direct sunlight.[14][15] Early detection through screening is useful for cervical and colorectal cancer.[16] The benefits of screening in breast cancer are controversial.[16][17] Cancer is often treated with some combination of radiation therapy, surgery, chemotherapy and targeted therapy.[2][4] Pain and symptom management are an important part of care.[2] Palliative care is particularly important in people with advanced disease.[2] The chance of survival depends on the type of cancer and extent of disease at the start of treatment.[11] In children under 15 at diagnosis, the five-year survival rate in the developed world is on average 80%.[18] For cancer in the United States, the average five-year survival rate is 66%.[5] In 2015, about 90.5 million people had cancer.[6] As of 2019, about 18 million new cases occur annually.[19] Annually, it caused about 8.8 million deaths (15.7% of deaths).[7] The most common types of cancer in males are lung cancer, prostate cancer, colorectal cancer, and stomach cancer.[20] In females, the most common types are breast cancer, colorectal cancer, lung cancer, and cervical cancer.[11] If skin cancer other than melanoma were included in total new cancer cases each year, it would account for around 40% of cases.[21][22] In children, acute lymphoblastic leukemia and brain tumors are most common, except in Africa, where non-Hodgkin lymphoma occurs more often.[18] In 2012, about 165,000 children under 15 years of age were diagnosed with cancer.[20] The risk of cancer increases significantly with age, and many cancers occur more commonly in developed countries.[11] Rates are increasing as more people live to an old age and as lifestyle changes occur in the developing world.[23] The financial costs of cancer were estimated at 1.16 trillion USD

Kaggle Challenge: Intel & MobileODT Cervical Cancer Screening

This project is held within a biomedical project course at Stanford University. We are working on the Kaggle Challenge: "Intel & MobileODT Cervical Cancer Screening" and we are building a Deep Learning model to classify cervix types.

ASCCP cervical cancer screening recommendations EMR integration

[SIGE-MII-UGR-2016-17] Repository for Kaggle Competition "Intel & MobileODT Cervical Cancer Screening"

Using pytorch for Intel & MobileODT Cervical Cancer Screening Kaggle challenge

https://www.kaggle.com/c/intel-mobileodt-cervical-cancer-screening

AI based system for cervical cancer screening by using PAP smear slides