EU-funded Researchers Tackle Cervical Cancer

Cervical cancer is the second most common cancer worldwide; each year some 60,000 women in Europe alone are diagnosed with the disease, and around half of these cases will prove fatal.Supported by the EU with EUR 2.63 million in funding, the ASSIST project aimed to fix this problem by creating technological links between medical centres specialising in cervical cancer diagnosis and treatment, as well as fuelling data exchange and building a larger data repository.

While scientists accept that the human papillomavirus (HPV) is the central risk factor for cervical cancer, they also recognise that HPV is not the only culprit. Researchers have been assessing the role of specific genetic and environmental factors in determining HPV-persistence and the subsequent progression of disease. Past studies have hinted at pathogenetic mechanisms that could provide new markers of risk, diagnosis and prognosis and potentially lead to new targets for treatment.

The ASSIST (Association studies assisted by inference and semantic technologies) project set out to combine the different kinds of data gathered by the researchers; automate the process of evaluating medical hypotheses; provide an inference engine capable of assessing material statistically; bring together the patient records repositories of the participating institutions; and develop graphical, expressive tools for medical researchers to post their queries.

Medical researchers use association studies to identify common factors behind diseases. They assess clinical data from hospital tests, lifestyle data (e.g. smoking and eating habits) and genetic data. The researchers also compare data from patients with that of healthy patients.

"What we are trying to do is to allow medical researchers working in specialist hospitals and medical centres to use each others" data, and combine the data into a bigger pool to work with,' Professor Pericles Mitkas of the Centre for Research and Technology - Hellas, Informatics and Telematics Institute, Greece said. "The problem is, each hospital uses different formats, different rules for storing data, even for exactly the same tests,' the project coordinator said. 'Even within hospitals, each doctor might have his or her own way of doing things."

Professor Mitkas noted that to date the greatest achievement of ASSIST was strengthening the dialogue between medical doctors, molecular biologists and computer scientists. "They are talking to each other and finally understanding each others' technical language," he explained.

Three hospitals from Belgium, Germany and Greece took part in the first part of the project. After agreeing on the common terminology and how the data should be represented and accessed, the research team developed a prototype software platform that ensures researchers receive data that are in the format requested. "We do this by semantic representation, which means we assign an interpretation to each value to help the computer understand what each value refers to," the project leader said.

"We also facilitate interpretation of subjective values like 'high risk' and 'low risk', 'serious cases' and 'non-serious cases', and use inferencing techniques which are based on a set of medical rules provided by doctors to tell the computer which results are more valid than others," he said. "Biopsy results, for example, are more conclusive than Pap test results and may point to a pre-cancer stage that a Pap test did not reveal."

The ASSIST prototype platform gave researchers access to patients' records at the three hospitals' departments of gynaecology and obstetrics. "We add extra functionality as we go along, but at least the doctors now have something to work with and evaluate," Professor Mitkas said.

"Further down the line, understanding the path to the disease and the factors that affect it will help individual doctors diagnose it earlier, prevent it by giving directions to their patients, and develop drugs or procedures that will cure the disease," he said. "But ASSIST is primarily a tool for medical researchers, and the results of their research will benefit all women."

For further information, please visit:
http://assist.ee.auth.gr

Related article:

Copyright ©European Communities, 2009
Neither the Office for Official Publications of the European Communities, nor any person acting on its behalf, is responsible for the use, which might be made of the attached information. The attached information is drawn from the Community R&D Information Service (CORDIS). The CORDIS services are carried on the CORDIS Host in Luxembourg - http://cordis.europa.eu. Access to CORDIS is currently available free-of-charge.

Most Popular Now

AI Catches One-Third of Interval Breast …

An AI algorithm for breast cancer screening has potential to enhance the performance of digital breast tomosynthesis (DBT), reducing interval cancers by up to one-third, according to a study published...

Great plan: Now We need to Get Real abou…

The government's big plan for the 10 Year Health Plan for the NHS laid out a big role for delivery. However, the Highland Marketing advisory board felt the missing implementation...

Researchers Create 'Virtual Scienti…

There may be a new artificial intelligence-driven tool to turbocharge scientific discovery: virtual labs. Modeled after a well-established Stanford School of Medicine research group, the virtual lab is complete with an...

From WebMD to AI Chatbots: How Innovatio…

A new research article published in the Journal of Participatory Medicine unveils how successive waves of digital technology innovation have empowered patients, fostering a more collaborative and responsive health care...

New AI Tool Accelerates mRNA-Based Treat…

A new artificial intelligence (AI) model can improve the process of drug and vaccine discovery by predicting how efficiently specific mRNA sequences will produce proteins, both generally and in various...

AI also Assesses Dutch Mammograms Better…

AI is detecting tumors more often and earlier in the Dutch breast cancer screening program. Those tumors can then be treated at an earlier stage. This has been demonstrated by...

RSNA AI Challenge Models can Independent…

Algorithms submitted for an AI Challenge hosted by the Radiological Society of North America (RSNA) have shown excellent performance for detecting breast cancers on mammography images, increasing screening sensitivity while...

AI could Help Emergency Rooms Predict Ad…

Artificial intelligence (AI) can help emergency department (ED) teams better anticipate which patients will need hospital admission, hours earlier than is currently possible, according to a multi-hospital study by the...

Head-to-Head Against AI, Pharmacy Studen…

Students pursuing a Doctor of Pharmacy degree routinely take - and pass - rigorous exams to prove competency in several areas. Can ChatGPT accurately answer the same questions? A new...

NHS Active 10 Walking Tracker Users are …

Users of the NHS Active 10 app, designed to encourage people to become more active, immediately increased their amount of brisk and non-brisk walking upon using the app, according to...

New AI Tool Illuminates "Dark Side…

Proteins sustain life as we know it, serving many important structural and functional roles throughout the body. But these large molecules have cast a long shadow over a smaller subclass...

Deep Learning-Based Model Enables Fast a…

Stroke is the second leading cause of death globally. Ischemic stroke, strongly linked to atherosclerotic plaques, requires accurate plaque and vessel wall segmentation and quantification for definitive diagnosis. However, conventional...