Naslov
Automatic recognition of self-acknowledged limitations in clinical research literature

Autori
Kilicoglu, Halil ; Rosemblat, Graciela ; Malički, Mario ; ter Riet, Gerben

Izvornik
Journal of the american medical informatics association (1067-5027) 25 (2018), 7; 855-861

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
self-acknowledged limitations ; clinical research literature ; natural language processing ; research transparency

Sažetak
Objective: To automatically recognize self- acknowledged limitations in clinical research publications to support efforts in improving research transparency. Methods: To develop our recognition methods, we used a set of 8431 sentences from 1197 PubMed Central articles. A subset of these sentences was manually annotated for training/testing, and inter-annotator agreement was calculated. We cast the recognition problem as a binary classification task, in which we determine whether a given sentence from a publication discusses self- acknowledged limitations or not. We experimented with three methods: a rule-based approach based on document structure, supervised machine learning, and a semi-supervised method that uses self- training to expand the training set in order to improve classification performance. The machine learning algorithms used were logistic regression (LR) and support vector machines (SVM). Results: Annotators had good agreement in labeling limitation sentences (Krippendorff's alpha = 0.781). Of the three methods used, the rule-based method yielded the best performance with 91.5% accuracy (95% CI [90.1-92.9]), while self-training with SVM led to a small improvement over fully supervised learning (89.9%, 95% CI [88.4- 91.4] vs 89.6%, 95% CI [88.1-91.1]). Conclusions: The approach presented can be incorporated into the workflows of stakeholders focusing on research transparency to improve reporting of limitations in clinical studies.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti

POVEZANOST RADA