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

Unlocking the 10 Year Health Plan

The government's plan for the NHS is a huge document. Jane Stephenson, chief executive of SPARK TSL, argues the key to unlocking its digital ambitions is to consider what it...

Alcidion Grows Top Talent in the UK, wit…

Alcidion has today announced the addition of three new appointments to their UK-based team, with one internal promotion and two external recruits. Dr Paul Deffley has been announced as the...

AI can Find Cancer Pathologists Miss

Men assessed as healthy after a pathologist analyses their tissue sample may still have an early form of prostate cancer. Using AI, researchers at Uppsala University have been able to...

AI, Full Automation could Expand Artific…

Automated insulin delivery (AID) systems such as the UVA Health-developed artificial pancreas could help more type 1 diabetes patients if the devices become fully automated, according to a new review...

How AI could Speed the Development of RN…

Using artificial intelligence (AI), MIT researchers have come up with a new way to design nanoparticles that can more efficiently deliver RNA vaccines and other types of RNA therapies. After training...

MIT Researchers Use Generative AI to Des…

With help from artificial intelligence, MIT researchers have designed novel antibiotics that can combat two hard-to-treat infections: drug-resistant Neisseria gonorrhoeae and multi-drug-resistant Staphylococcus aureus (MRSA). Using generative AI algorithms, the research...

AI Hybrid Strategy Improves Mammogram In…

A hybrid reading strategy for screening mammography, developed by Dutch researchers and deployed retrospectively to more than 40,000 exams, reduced radiologist workload by 38% without changing recall or cancer detection...

Penn Developed AI Tools and Datasets Hel…

Doctors treating kidney disease have long depended on trial-and-error to find the best therapies for individual patients. Now, new artificial intelligence (AI) tools developed by researchers in the Perelman School...

New Training Year Starts at Siemens Heal…

In September, 197 school graduates will start their vocational training or dual studies in Germany at Siemens Healthineers. 117 apprentices and 80 dual students will begin their careers at Siemens...

Are You Eligible for a Clinical Trial? C…

A new study in the academic journal Machine Learning: Health discovers that ChatGPT can accelerate patient screening for clinical trials, showing promise in reducing delays and improving trial success rates. Researchers...

New AI Tool Addresses Accuracy and Fairn…

A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases in datasets used to train machine-learning algorithms...

Global Study Reveals How Patients View M…

How physicians feel about artificial intelligence (AI) in medicine has been studied many times. But what do patients think? A team led by researchers at the Technical University of Munich...