Challenges on Biomedical Information Retrieval and Question Answering

Every day, approximately 3000 new articles are published in biomedical journals. That averages to more than 2 articles every minute. Managing this large amount of data is a challenge in itself. Yet, ensuring that this wealth of knowledge is used for the sake of the patients in a timely manner is an even more demanding task for both computer scientists and biomedical experts.

The BioASQ project, which started on October 1st 2012 and runs for 2 years, aims to push research in information technology towards highly precise biomedical information retrieval systems. The project will achieve this goal through a competition (challenge), in which systems from teams around the world will compete. BioASQ will provide the data, software, hardware and the evaluation infrastructure for the challenge. By these means, the project will ensure that the biomedical experts of the future can rely on software tools to identify, process and present the fragments of the huge space of biomedical resources that address their personal questions.

The tasks included in the BioASQ challenges will help advance the state of the art in two fields. First, the automatic classification of biomedical documents will be improved. Here, systems will be required to tag large numbers of scientific biomedical articles with terms from a predefined biomedical vocabulary. Additionally, the challenge will evaluate how well systems identify text fragments in scientific articles, and related data in public knowledge bases, in order to answer questions set by the European biomedical expert team of BioASQ.

Further results of the project will include a set of open-source tools and a social network that will support experts in setting up similar challenges, beyond the end of the project.

The BioASQ team combines researchers with complementary expertise from 6 organisations in 3 countries: the Greek National Center for Scientific Research "Demokritos" (coordinator), participating with its Institutes of 'Informatics & Telecommunications' and 'Biosciences & Applications', the German IT company Transinsight GmbH, the French University Joseph Fourier, the German research Group for Agile Knowledge Engineering and Semantic Web at the University of Leipzig, the French University Pierre et Marie Curie-Paris 6 and the Research Center of the Athens University of Economics and Business in Greece. Moreover, biomedical experts from several countries assist in the creation of the evaluation data and a number of key players in the industry and academia from around the world participate in the advisory board of the project.

For further information, please visit:
http://www.bioasq.org

Most Popular Now

Philips Foundation 2024 Annual Report: E…

Marking its tenth anniversary, Philips Foundation released its 2024 Annual Report, highlighting a year in which the Philips Foundation helped provide access to quality healthcare for 46.5 million people around...

New AI Transforms Radiology with Speed, …

A first-of-its-kind generative AI system, developed in-house at Northwestern Medicine, is revolutionizing radiology - boosting productivity, identifying life-threatening conditions in milliseconds and offering a breakthrough solution to the global radiologist...

Scientists Argue for More FDA Oversight …

An agile, transparent, and ethics-driven oversight system is needed for the U.S. Food and Drug Administration (FDA) to balance innovation with patient safety when it comes to artificial intelligence-driven medical...

New Research Finds Specific Learning Str…

If data used to train artificial intelligence models for medical applications, such as hospitals across the Greater Toronto Area, differs from the real-world data, it could lead to patient harm...

Giving Doctors an AI-Powered Head Start …

Detection of melanoma and a range of other skin diseases will be faster and more accurate with a new artificial intelligence (AI) powered tool that analyses multiple imaging types simultaneously...

AI Agents for Oncology

Clinical decision-making in oncology is challenging and requires the analysis of various data types - from medical imaging and genetic information to patient records and treatment guidelines. To effectively support...

Patients say "Yes..ish" to the…

As artificial intelligence (AI) continues to be integrated in healthcare, a new multinational study involving Aarhus University sheds light on how dental patients really feel about its growing role in...

Brains vs. Bytes: Study Compares Diagnos…

A University of Maine study compared how well artificial intelligence (AI) models and human clinicians handled complex or sensitive medical cases. The study published in the Journal of Health Organization...

'AI Scientist' Suggests Combin…

An 'AI scientist', working in collaboration with human scientists, has found that combinations of cheap and safe drugs - used to treat conditions such as high cholesterol and alcohol dependence...

Start-ups in the Spotlight at MEDICA 202…

17 - 20 November 2025, Düsseldorf, Germany. MEDICA, the leading international trade fair and platform for healthcare innovations, will once again confirm its position as the world's number one hotspot for...