A reproducible approach with R markdown to automatic classification of medical certificates in French

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 this Task which promotes the sharing of tools and the dissemination of solid, reproducible results.In questo articolo presentiamo gli sviluppi del lavoro iniziato con la partecipazione al Laboratorio CrossLanguage Evaluation Forum (CLEF) eHealth denominato: “Multilingual Information Extraction - ICD10 coding” (Névéol et al., 2017) che ha come obiettivo quello di classificare certificati di morte in lingua francese con dei codici standard internazionali. In particolare, abbiamo come obiettivo quello proposto dalla ‘Replication track’ di questo Task, che promuove la condivisione di strumenti e la diffusione di risultati riproducibili

The Benefits of Word Embeddings Features for Active Learning in Clinical Information Extraction

This study investigates the use of unsupervised word embeddings and sequence features for sample representation in an active learning framework built to extract clinical concepts from clinical free text. The objective is to further reduce the manual annotation effort while achieving higher effectiveness compared to a set of baseline features. Unsupervised features are derived from skip-gram word embeddings and a sequence representation approach. The comparative performance of unsupervised features and baseline hand-crafted features in an active learning framework are investigated using a wide range of selection criteria including least confidence, information diversity, information density and diversity, and domain knowledge informativeness. Two clinical datasets are used for evaluation: the i2b2/VA 2010 NLP challenge and the ShARe/CLEF 2013 eHealth Evaluation Lab. Our results demonstrate significant improvements in terms of effectiveness as well as annotation effort savings across both datasets. Using unsupervised features along with baseline features for sample representation lead to further savings of up to 9% and 10% of the token and concept annotation rates, respectively

LITL at CLEF eHealth2016: recognizing entities in French biomedical documents

International audienceThis paper describes the participation of master's students (LITL programme, university of Toulouse) and their teachers to the CLEF eHealth 2016 campaign. Two runs were submitted for task 2 (multilingual information extraction) which consisted in the recognition and categorization of medical entities in French biomedical documents. The system used consists of a CRF classier based on a number of dierent features (POS tagging, generic word lists and syntactic parsing). In addition , several patterns were used on the CRF's output in order to extract more complex entities. The best run achieved high precision (0.640.78) but lower recall (0.320.40), with an overall F1-measure of 0.430.53

Search strategy formulation for systematic reviews: Issues, challenges and opportunities

Systematic literature reviews play a vital role in identifying the best available evidence for health and social care research, policy, and practice. The resources required to produce systematic reviews can be significant, and a key to the success of any review is the search strategy used to identify relevant literature. However, the methods used to construct search strategies can be complex, time consuming, resource intensive and error prone. In this review, we examine the state of the art in resolving complex structured information needs, focusing primarily on the healthcare context. We analyse the literature to identify key challenges and issues and explore appropriate solutions and workarounds. From this analysis we propose a way forward to facilitate trust and to aid explainability and transparency, reproducibility and replicability through a set of key design principles for tools to support the development of search strategies in systematic literature reviews