Artificial Intelligence for Early Cervical Cancer Diagnosis

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To build an App for Papanicolau Smears diagnosis, to early detect Cervical Cancer

The project
Who is behind

Cervical cancer is one of the most incapacitating cancers over the World. It’s the fourth cancer between women, the sixth in Europe and the most frequent over 28 developing countries.

In developing countries, cervical cancer is the first cancer that cause death in women, even more than breast cancer.

This cancer appears by the developing of tumoral cells in cervical cancer due to Human Papilloma Virus (HPV) infection, often by sexual transmission. Uterin cervix is the part of the uterus that connects it to vagina.

The medium age at the diagnosis is 48 years, but almost the half part of invasive cervical cancer cases appears before 35. Only the 10% of cases are diagnosed over 65 years old, and cases in younger women are nowadays increasing.

Its early detection is possible by the use and analysis of Papanicolau Cervical Smears. This is a diagnostic tool that consists in sampling the superficial epithelium from uterin cervix to analyze it, detecting cellular changes related with HPV infection that could lead to cervical cancer in the future. However, in Spain there is no Population Screening Program to study all women such are in other countries as Australia or the UK, partially due to the high amount of samples to analyze.

 

What is our goal?

The main objective in this proyect is to develop a Computer Asisted Diagnosis system to help Doctors to early diagnose pathologic changes in cells from a Papanicolaou smear sample, by Artificial Intelligence applicated over their optic characteristics analysis. This system could automatically manage a big volume of smears, detecting pathologic samples, so, the Pathologists would only have to check these, reducing near the 85% of their work load comparing with the classic way.

This system pretends to be a useful tool to plan population screening programs, allowing for decreasing this cancer incidence and its effects.

This tool could be applied in all Pathology Labs where a microscopic samples scanner is available, and could analyze thousand of samples per year, optimizing the diagnosis process.

Our team has developed a prior work, obtaining similar diagnostic results than expert pathologists have (85-98’8%). But to be able to apply these algorithms to real patients diagnostic, to increase the dataset, perform a higher amount of tests, try different algorithms and develop a computer application  is required. These algorithms not only detect abnormal smears, but could locate the cells and the region of interest in the sample to be checked by the Pathologist.

Who will benefit from our project?

All women who perform a Papanicolau cervical smear could be beneficiary of this work results.

This project could open the chance to create population screening programs for early cervical cancer diagnosis, that doesn’t exist in Spain. It would enhance the diagnostic capability of Pathology Labs that use it, improving cervical cancer detection and its previous lesions, decreasing this cancer incidence and its effects.

Do you want more information?

 

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28100 Alcobendas (Madrid) - España
T.+(00 34) 91 425 09 09
info@precipita.es
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