Ranking Significant Discrepancies in Clinical Reports

Medical errors are a major public health concern and a leading cause of death worldwide. Many healthcare centers and hospitals use reporting systems where medical practitioners write a preliminary medical report and the report is later reviewed, revised, and finalized by a more experienced physician. The revisions range from stylistic to corrections of critical errors or misinterpretations of the case. Due to the large quantity of reports written daily, it is often difficult to manually and thoroughly review all the finalized reports to find such errors and learn from them. To address this challenge, we propose a novel ranking approach, consisting of textual and ontological overlaps between the preliminary and final versions of reports. The approach learns to rank the reports based on the degree of discrepancy between the versions. This allows medical practitioners to easily identify and learn from the reports in which their interpretation most substantially differed from that of the attending physician (who finalized the report). This is a crucial step towards uncovering potential errors and helping medical practitioners to learn from such errors, thus improving patient-care in the long run. We evaluate our model on a dataset of radiology reports and show that our approach outperforms both previously-proposed approaches and more recent language models by 4.5% to 15.4%.Comment: ECIR 2020 (short

Ontologies for Legal Relevance and Consumer Complaints. A Case Study in the Air Transport Passenger Domain

Applying relevant legal information to settle complaints and disputes is a common challenge for all legal practitioners and laymen. However, the analysis of the concept of relevance itself has thus far attracted only sporadic attention. This thesis bridges this gap by understanding the components of complaints, and by defining relevant legal information, and makes use of computational ontologies and design patterns to represent this relevant knowledge in an explicit and structured way. This work uses as a case-study a real situation of consumer disputes in the Air Transport Passenger domain. Two artifacts were built: the Relevant Legal Information in Consumer Disputes Ontology, and its specialization, the Air Transport Passenger Incidents Ontology, aimed at modelling relevant legal information; and the Complaint Design Pattern proposed to conceptualize complaints. In order to demonstrate the ability of the ontologies to serve as a knowledge base for a computer program providing relevant legal information, a demonstrative application was developed