This paper describes the findings of an exploratory study on reverse mapping of ICD-10-CA, the Canadian Adaptation, to SNOMED CT. For this study a set of 5,000 most frequent ICD-10-CA codes from the health ministry of a Canadian province was used. The methods included applying six mapping algorithms to each ICD-10-CA description to find the matching SNOMED CT concepts, and comparing the output ...

Unlike recent biomedical terminologies, the International Classification of Diseases (ICD) does not state any explicit associations between a given disease and the corresponding anatomical structure(s). As a consequence, clinical repositories coded with ICD cannot be searched by anatomical structure. The objective of this work is to find associations between diseases from ICD10 and anatomical s...

In this work we leverage crowdsourcing in connection with machine learning techniques to validate candidate ICD10 Code to UMLS concept relationships that we generate. Our immediate use is in natural language understanding and machine learning approaches to automatically code electronic health record documents with ICD codes. Beyond auto-coding, the relationships will aid a wide variety of futur...

With many hospitals digitalizing clinical records it has opened opportunities for researchers in NLP, Machine Learning to apply techniques for extracting meaning and make actionable insights. There has been previous attempts in mapping free text to medical nomenclature like UMLS, SNOMED. However, in this paper, we analyzed diagnosis in clinical reports by mapping into ICD10 codes. We propose a ...

BACKGROUND The aim of this study was to examine the expression of CD10 and CD15 in tumor cells, stromal cells and infiltrating inflammatory cells during colorectal carcinoma (CRC) development and to investigate their expression levels between the tumor center and invasive front and compare them to clinicopathological parameters in invasive CRC. METHODS We performed immunohistochemical stainin...

English. In this paper, we report the ongoing developments of our first participation to the Cross-Language Evaluation Forum (CLEF) eHealth Task 1: “Multilingual Information Extraction ICD10 coding” (Névéol et al., 2017). The task consists in labelling death certificates, in French with international standard codes. In particular, we wanted to accomplish the goal of the ‘Replication track’ of t...

We describe LIMSI experiments in ICD10 coding of death certificate statements with the CépiDc dataset of the CLEF eHealth 2016 Track 2. We tested a classifier with humanly-interpretable output, based on IR-style ranking of candidate ICD10 diagnoses. A tf.idf-weighted bagof-feature vector was built for each training set code by merging all the statements found for this code in the training data....

BACKGROUND With the 11th revision of the International Classification of Disease (ICD) being officially launched by the World Health Organization (WHO), the significance of a formal representation for ICD coding rules has emerged as a pragmatic concern. OBJECTIVES To explore the role of Formal Concept Analysis (FCA) on examining ICD10 coding rules and to develop FCA-based auditing approaches ...

BACKGROUND Because of their individual rarity, genetic diseases and other types of rare diseases are under-represented in healthcare coding systems; this contributes to a lack of ascertainment and recognition of their importance for healthcare planning and resource allocation, and prevents clinical research from being performed. METHODS Orphanet was given the task to develop an inventory of r...