1,214 research outputs found
Robotic Faces: Exploring Dynamical Patterns of Social Interaction between Humans and Robots
Thesis (Ph.D.) - Indiana University, Informatics, 2015The purpose of this dissertation is two-fold: 1) to develop an empirically-based design for an interactive robotic face, and 2) to understand how dynamical aspects of social interaction may be leveraged to design better interactive technologies and/or further our understanding of social cognition.
Understanding the role that dynamics plays in social cognition is a challenging problem. This is particularly true in studying cognition via human-robot interaction, which entails both the natural social cognition of the human and the “artificial intelligence” of the robot. Clearly, humans who are interacting with other humans (or even other mammals such as dogs) are cognizant of the social nature of the interaction – their behavior in those cases differs from that when interacting with inanimate objects such as tools. Humans (and many other animals) have some awareness of “social”, some sense of other agents. However, it is not clear how or why.
Social interaction patterns vary across culture, context, and individual characteristics of the human interactor. These factors are subsumed into the larger interaction system, influencing the unfolding of the system over time (i.e. the dynamics). The overarching question is whether we can figure out how to utilize factors that influence the dynamics of the social interaction in order to imbue our interactive technologies (robots, clinical AI, decision support systems, etc.) with some "awareness of social", and potentially create more natural interaction paradigms for those technologies.
In this work, we explore the above questions across a range of studies, including lab-based experiments, field observations, and placing autonomous, interactive robotic faces in public spaces. We also discuss future work, how this research relates to making sense of what a robot "sees", creating data-driven models of robot social behavior, and development of robotic face personalities
A Reanalysis of Eurasian Population History: Ancient DNA Evidence of Population Affinities
Mitochondrial hypervariable region I genetic data from ancient populations at
two sites from Asia, Linzi in Shandong (northern China) and Egyin Gol in
Mongolia, were reanalyzed to detect population affinities. Data from a total of
51 modern populations were used to generate distance measures (Fst's) to the
two ancient populations. The tests first analyzed relationships at the regional
level, and then compiled the top regional matches for an overall comparison to
the two probe populations. The reanalysis showed that the Egyin Gol and Linzi
populations have clear distinctions in genetic affinity. The Egyin Gol
population as a whole appears to bear close affinities with modern populations
of northern East Asia. The Linzi population does seem to have some genetic
affinities with the West as suggested by the original analysis, though the
original attribution of "European-like" seems to be misleading. This study
suggests that the Linzi individuals are potentially related to early Iranians,
who are thought to have been widespread in parts of Central Eurasia and the
steppe regions in the first millennium BC, though some significant admixture
between a number of populations of varying origin cannot be ruled out. The
study also examines the effect of sequence length on this type of genetic data
analysis and provides analysis and explanation for the results of previous
studies on the Linzi sample as compared to this one.Comment: Keywords: d-loop, China, Mongolia, aDNA, mtDNA, Irania
EHRs Connect Research and Practice: Where Predictive Modeling, Artificial Intelligence, and Clinical Decision Support Intersect
Objectives: Electronic health records (EHRs) are only a first step in
capturing and utilizing health-related data - the challenge is turning that
data into useful information. Furthermore, EHRs are increasingly likely to
include data relating to patient outcomes, functionality such as clinical
decision support, and genetic information as well, and, as such, can be seen as
repositories of increasingly valuable information about patients' health
conditions and responses to treatment over time. Methods: We describe a case
study of 423 patients treated by Centerstone within Tennessee and Indiana in
which we utilized electronic health record data to generate predictive
algorithms of individual patient treatment response. Multiple models were
constructed using predictor variables derived from clinical, financial and
geographic data. Results: For the 423 patients, 101 deteriorated, 223 improved
and in 99 there was no change in clinical condition. Based on modeling of
various clinical indicators at baseline, the highest accuracy in predicting
individual patient response ranged from 70-72% within the models tested. In
terms of individual predictors, the Centerstone Assessment of Recovery Level -
Adult (CARLA) baseline score was most significant in predicting outcome over
time (odds ratio 4.1 + 2.27). Other variables with consistently significant
impact on outcome included payer, diagnostic category, location and provision
of case management services. Conclusions: This approach represents a promising
avenue toward reducing the current gap between research and practice across
healthcare, developing data-driven clinical decision support based on
real-world populations, and serving as a component of embedded clinical
artificial intelligences that "learn" over time.Comment: Keywords: Data Mining; Decision Support Systems, Clinical; Electronic
Health Records; Implementation; Evidence-Based Medicine; Data Warehouse;
(2012). EHRs Connect Research and Practice: Where Predictive Modeling,
Artificial Intelligence, and Clinical Decision Support Intersect. Health
Policy and Technology. arXiv admin note: substantial text overlap with
arXiv:1112.166
Utilizing RxNorm to Support Practical Computing Applications: Capturing Medication History in Live Electronic Health Records
RxNorm was utilized as the basis for direct-capture of medication history
data in a live EHR system deployed in a large, multi-state outpatient
behavioral healthcare provider in the United States serving over 75,000
distinct patients each year across 130 clinical locations. This tool
incorporated auto-complete search functionality for medications and proper
dosage identification assistance. The overarching goal was to understand if and
how standardized terminologies like RxNorm can be used to support practical
computing applications in live EHR systems. We describe the stages of
implementation, approaches used to adapt RxNorm's data structure for the
intended EHR application, and the challenges faced. We evaluate the
implementation using a four-factor framework addressing flexibility, speed,
data integrity, and medication coverage. RxNorm proved to be functional for the
intended application, given appropriate adaptations to address high-speed
input/output (I/O) requirements of a live EHR and the flexibility required for
data entry in multiple potential clinical scenarios. Future research around
search optimization for medication entry, user profiling, and linking RxNorm to
drug classification schemes holds great potential for improving the user
experience and utility of medication data in EHRs.Comment: Appendix (including SQL/DDL Code) available by author request.
Keywords: RxNorm; Electronic Health Record; Medication History;
Interoperability; Unified Medical Language System; Search Optimizatio
Physical activity in US Blacks: a systematic review and critical examination of self-report instruments
<p>Abstract</p> <p>Background</p> <p>Physical activity self-report instruments in the US have largely been developed for and validated in White samples. Despite calls to validate existing instruments in more diverse samples, relatively few instruments have been validated in US Blacks. Emerging evidence suggests that these instruments may have differential validity in Black populations.</p> <p>Purpose</p> <p>This report reviews and evaluates the validity and reliability of self-reported measures of physical activity in Blacks and makes recommendations for future directions.</p> <p>Methods</p> <p>A systematic literature review was conducted to identify published reports with construct or criterion validity evaluated in samples that included Blacks. Studies that reported results separately for Blacks were examined.</p> <p>Results</p> <p>The review identified 10 instruments validated in nine manuscripts. Criterion validity correlations tended to be low to moderate. No study has compared the validity of multiple instruments in a single sample of Blacks.</p> <p>Conclusion</p> <p>There is a need for efforts validating self-report physical activity instruments in Blacks, particularly those evaluating the relative validity of instruments in a single sample.</p
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