Institution
City University London
Education•London, United Kingdom•
About: City University London is a education organization based out in London, United Kingdom. It is known for research contribution in the topics: Population & Health care. The organization has 5735 authors who have published 17285 publications receiving 453290 citations.
Papers published on a yearly basis
Papers
More filters
••
21 Apr 2018TL;DR: This work explores how the biased contents of databases, the syntactic focus of natural language processing, and the opaque nature of deep learning algorithms cause chatbots difficulty in handling race-talk.
Abstract: Why is it so hard for chatbots to talk about race? This work explores how the biased contents of databases, the syntactic focus of natural language processing, and the opaque nature of deep learning algorithms cause chatbots difficulty in handling race-talk. In each of these areas, the tensions between race and chatbots create new opportunities for people and machines. By making the abstract and disparate qualities of this problem space tangible, we can develop chatbots that are more capable of handling race-talk in its many forms. Our goal is to provide the HCI community with ways to begin addressing the question, how can chatbots handle race-talk in new and improved ways?
124 citations
••
TL;DR: A critical appreciation of the theory that the recall of an event entails a generation (or search) process followed by a recognition (or decision) process is given in this article. But the results of a large number of studies run counter to its predictions or are otherwise not readily accommodated by it.
124 citations
••
Radboud University Nijmegen1, Katholieke Universiteit Leuven2, University Medical Center Utrecht3, Bosch4, Hospital Universitario La Paz5, Charité6, Karolinska University Hospital7, University of Antwerp8, Princess Alexandra Hospital9, Griffith University10, City University London11, Canberra Hospital12, University of Southampton13
TL;DR: Patients’ delirium risk for the complete ICU length of stay can be predicted at admission using the E-PRE-DELIRIC model, allowing early preventive interventions aimed to reduce incidence and severity of ICU deliria.
Abstract: Rationale
Delirium incidence in intensive care unit (ICU) patients is high and associated with poor outcome. Identification of high-risk patients may facilitate its prevention.
123 citations
••
01 Jan 2012123 citations
••
TL;DR: The PI20; a 20-item self-report measure for quantifying prosopagnosic traits is introduced; the new instrument successfully distinguishes suspected prosOPagnosics from typically developed adults and did not correlate with recognition of non-face objects, indicating that the instrument measures face recognition, and not a general perceptual impairment.
Abstract: Self-report plays a key role in the identification of developmental prosopagnosia (DP), providing complementary evidence to computer-based tests of face recognition ability, aiding interpretation of scores. However, the lack of standardized self-report instruments has contributed to heterogeneous reporting standards for self-report evidence in DP research. The lack of standardization prevents comparison across samples and limits investigation of the relationship between objective tests of face processing and self-report measures. To address these issues, this paper introduces the PI20; a 20-item self-report measure for quantifying prosopagnosic traits. The new instrument successfully distinguishes suspected prosopagnosics from typically developed adults. Strong correlations were also observed between PI20 scores and performance on objective tests of familiar and unfamiliar face recognition ability, confirming that people have the necessary insight into their own face recognition ability required by a self-report instrument. Importantly, PI20 scores did not correlate with recognition of non-face objects, indicating that the instrument measures face recognition, and not a general perceptual impairment. These results suggest that the PI20 can play a valuable role in identifying DP. A freely available self-report instrument will permit more effective description of self-report diagnostic evidence, thereby facilitating greater comparison of prosopagnosic samples, and more reliable classification.
123 citations
Authors
Showing all 5822 results
Name | H-index | Papers | Citations |
---|---|---|---|
Andrew M. Jones | 103 | 764 | 37253 |
F. Rauscher | 100 | 605 | 36066 |
Thorsten Beck | 99 | 373 | 62708 |
Richard J. K. Taylor | 91 | 1543 | 43893 |
Christopher N. Bowman | 90 | 639 | 38457 |
G. David Batty | 88 | 451 | 23826 |
Xin Zhang | 87 | 1714 | 40102 |
Richard J. Cook | 84 | 571 | 28943 |
Hugh Willmott | 82 | 310 | 26758 |
Scott Reeves | 82 | 441 | 27470 |
Sarah-Jayne Blakemore | 81 | 211 | 29660 |
Mats Alvesson | 78 | 267 | 38248 |
W. John Edmunds | 75 | 252 | 24018 |
Sheng Chen | 71 | 688 | 27847 |
Christopher J. Taylor | 71 | 415 | 30948 |