Information Retrieval applied to the Medical Literature
Now-a-days health professionals might feel overwhelmed by the large amount of information that is available related to a certain medical condition. Every time they need to search in the literature for relevant information regarding a specific case (e.g. 38 years old patient, male with leukemia) might be an arduous task. The fields of information retrieval, natural language processing (NLP) and even machine learning can help easy this burden by providing methods to find the right literature automatically in a timely manner to the desired patient case. For example, by leveraging existent healthcare terminologies we can add synonyms for leukemia (such as leucaemia) to the patient case search and enhance the chance of finding relevant information in the literature. We could also find the most cited words related to a specific topic (e.g. cancer appears together with leukemia) in a set of relevant documents and use them as another attribute to make our search better. Therefore, with the help of computational methods, there are many possibilities to make the hard task of finding the right literature easier for health professionals.