The role of mobile computed tomography in mass fatality incidents

Mobile multi-detector computed tomography (MDCT) scanners are potentially available to temporary mortuaries and can be operational within 20 min of arrival. We describe, to our knowledge, the first use of mobile MDCT for a mass fatality incident. A mobile MDCT scanner attended the disaster mortuary after a five vehicle road traffic incident. Five out of six bodies were successfully imaged by MDCT in c. 15 min per body. Subsequent full radiological analysis took c. 1 h per case. The results were compared to the autopsy examinations. We discuss the advantages and disadvantages of imaging with mobile MDCT in relation to mass fatality work, illustrating the body pathway process, and its role in the identification of the pathology, personal effects, and health and safety hazards. We propose that the adoption of a single modality of mobile MDCT could replace the current use of multiple radiological sources within a mass fatality mortuary.     

Using Named Entities for Computer‐Automated Verbal Deception Detection

There is an increasing demand for automated verbal deception detection systems. We propose named entity recognition (NER; i.e., the automatic identification and extraction of information from text) to model three established theoretical principles: (i) truth tellers provide accounts that are richer in detail, (ii) contain more contextual references (specific persons, locations, and times), and (iii) deceivers tend to withhold potentially checkable information. We test whether NER captures these theoretical concepts and can automatically identify truthful versus deceptive hotel reviews. We extracted the proportion of named entities with two NER tools (spaCy and Stanford's NER) and compared the discriminative ability to a lexicon word count approach (LIWC) and a measure of sentence specificity (speciteller). Named entities discriminated truthful from deceptive hotel reviews above chance level, and outperformed the lexicon approach and sentence specificity. This investigation suggests that named entities may be a useful addition to existing automated verbal deception detection approaches.