NLP in healthcare: The power of AI-based systematic literature review

Learn how AI is transforming systematic literature review tools to improve precision, efficiency, and the future of research.
NLP in healthcare

Health professionals have always relied on systematic literature reviews (SLRs) to help them make sense of the vast amount of scientific information available. Whether you’re an experienced researcher in health economics and outcomes research (HEOR) or someone in charge of planning pharmaceutical studies, SLRs act as your guide through the complex world of biomedical literature. 

But in a world where new information is constantly emerging, can traditional, manual SLRs keep up? 

Understanding the SLR process  

SLRs are not just about gathering articles. They are a careful effort to bring together the best information on a topic in a clear and repeatable way. These reviews collect all the available insights on a subject, ensuring a balanced perspective, and then assess the quality of that information. The downside? Traditional SLRs require a significant investment of time and money. 

However, with the rapid pace of biomedical research, there’s a need for automation. This is where artificial intelligence (AI) and advanced technology solutions come into play. 

A new approach  

IMO’s systematic literature review tool draws on our extensive experience in mining biomedical literature. This solution is not just another digital platform. It covers every step in the SLR process, from setting up study guidelines (like defining which articles to include and exclude) to reviewing literature, extracting data, and even creating visual representations of the results. 

But what makes it unique? It uses cutting-edge natural language processing (NLP). 

During the initial screening of abstracts, our NLP model doesn’t just go through the data—it suggests which articles are worth a full-text review, providing specific reasons for its recommendations. When it’s time to extract data, a combination of deep learning and language rules delves into full-text articles, including complex tables, to find relevant information. And don’t worry; every suggestion made by AI is double-checked by human experts, ensuring a mix of machine efficiency and human insight. 

Bridging the gap with NLP  

Although our SLR solution has its roots in HEOR studies, it can adapt to different research areas. It can also integrate seamlessly into the existing workflows of major pharmaceutical companies, showcasing its versatility. 

See it for yourself 

Ready to dive deeper into the world of smart literature review? Learn from our team of experts how IMO’s AI-powered solution is changing the landscape of systematic literature review – offering accuracy, scalability, and efficiency across various therapeutic fields.  

Ideas are meant for sharing.

Sign up today and have Ideas delivered straight to your inbox.

Related Ideas