Improving Clinical Diagnosis Inference through Integration of Structured and Unstructured Knowledge
نویسندگان
چکیده
This paper presents a novel approach to the task of automatically inferring the most probable diagnosis from a given clinical narrative. Structured Knowledge Bases (KBs) can be useful for such complex tasks but not sufficient. Hence, we leverage a vast amount of unstructured free text to integrate with structured KBs. The key innovative ideas include building a concept graph from both structured and unstructured knowledge sources and ranking the diagnosis concepts using the enhanced word embedding vectors learned from integrated sources. Experiments on the TREC CDS and HumanDx datasets showed that our methods improved the results of clinical diagnosis inference.
منابع مشابه
The Challenges of Applying Theoretical Knowledge in the Clinical Settings: A Qualitative Study
Background & Objective: In recent years, insufficient clinical education and the lack of integration with theoretical knowledge has caused problems in patients’ care. This study aimed to identify the barriers of applying learned lessons in the classroom in clinical settings Materials and Methods: A qualitative content analysis approach was adopted. Individual semi-structured interviews with cl...
متن کاملInformation Extraction in Medical Domain Using Ontology and Knowledge Graphs
Medical documents contain lots of information which can be useful to build many health related applications. Since medical documents present unstructured information in nonstandard natural language so it is difficult to extract this information and present in a structured manner. We propose a model named "Feature Based Relation Extraction with Relational Learning using Medical Ontology" which m...
متن کاملREMIND: A Bayesian Framework for Reliable Extraction and Meaningful Inference from Non-structured Data
Existing patient records are a valuable resource for automated outcomes analysis and knowledge discovery. However, key clinical data in these records is typically recorded in unstructured form as free text and images, and most structured clinical information is poorly organized. Time-consuming interpretation and analysis is required to convert these records into structured clinical data. Thus, ...
متن کاملData integration for inference about spatial processes: A model-based approach to test and account for data inconsistency
Recently-developed methods that integrate multiple data sources arising from the same ecological processes have typically utilized structured data from well-defined sampling protocols (e.g., capture-recapture and telemetry). Despite this new methodological focus, the value of opportunistic data for improving inference about spatial ecological processes is unclear and, perhaps more importantly, ...
متن کاملQuestion Answering via Integer Programming over Semi-Structured Knowledge
Answering science questions posed in natural language is an important AI challenge. Answering such questions often requires non-trivial inference and knowledge that goes beyond factoid retrieval. Yet, most systems for this task are based on relatively shallow Information Retrieval (IR) and statistical correlation techniques operating on large unstructured corpora. We propose a structured infere...
متن کامل