Improving Medical Information Retrieval with PICO Element Detection
نویسندگان
چکیده
Without a well formulated and structured question, it can be very difficult and time consuming for physicians to identify appropriate resources and search for the best available evidence for medical treatment in evidence-based medicine (EBM). In EBM, clinical studies and questions involve four aspects: Population/Problem (P), Intervention (I), Comparison (C) and Outcome (O), which are known as PICO elements. It is intuitively more advantageous to use these elements in Information Retrieval (IR). In this paper, we first propose an approach to automatically identify the PICO elements in documents and queries. We test several possible approaches to use the identified elements in IR. Experiments show that it is a challenging task to determine accurately PICO elements. However, even with noisy tagging results, we can still take advantage of some PICO elements, namely I and P elements, to enhance the retrieval process, and this allows us to obtain significantly better retrieval effectiveness than the state-of-the-art methods.
منابع مشابه
Combining classifiers for robust PICO element detection
BACKGROUND Formulating a clinical information need in terms of the four atomic parts which are Population/Problem, Intervention, Comparison and Outcome (known as PICO elements) facilitates searching for a precise answer within a large medical citation database. However, using PICO defined items in the information retrieval process requires a search engine to be able to detect and index PICO ele...
متن کاملDevelopment of a Search Strategy for an Evidence Based Retrieval Service
BACKGROUND Physicians are often encouraged to locate answers for their clinical queries via an evidence-based literature search approach. The methods used are often not clearly specified. Inappropriate search strategies, time constraint and contradictory information complicate evidence retrieval. AIMS Our study aimed to develop a search strategy to answer clinical queries among physicians in ...
متن کاملSteganography Scheme Based on Reed-Muller Code with Improving Payload and Ability to Retrieval of Destroyed Data for Digital Images
In this paper, a new steganography scheme with high embedding payload and good visual quality is presented. Before embedding process, secret information is encoded as block using Reed-Muller error correction code. After data encoding and embedding into the low-order bits of host image, modulus function is used to increase visual quality of stego image. Since the proposed method is able to embed...
متن کاملClinical Information Retrieval using Document and PICO Structure
In evidence-based medicine, clinical questions involve four aspects: Patient/Problem (P), Intervention (I), Comparison (C) and Outcome (O), known as PICO elements. In this paper we present a method that extends the language modeling approach to incorporate both document structure and PICO query formulation. We present an analysis of the distribution of PICO elements in medical abstracts that mo...
متن کاملRépondre à des requêtes cliniques PICO
In this paper, we address the issue of answering PICO (Patient/Problem, Intervention, Comparison, Outcome) clinical queries. The contributions of this work include (1) a new document ranking model based on a prioritized aggregation operator that computes the global relevance score based on the relevance estimation of the semantic facet sub-queries and (2) leverages the importance of the facets ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2010