Physiological Indicators for User Trust in Machine Learning with Influence Enhanced Fact-Checking

© IFIP International Federation for Information Processing 2019. Trustworthy Machine Learning (ML) is one of significant challenges of “black-box” ML for its wide impact on practical applications. This paper investigates the effects of presentation of influence of training data points on machine learning predictions to boost user trust. A framework of fact-checking for boosting user trust is proposed in a predictive decision making scenario to allow users to interactively check the training data points with different influences on the prediction by using parallel coordinates based visualization. This work also investigates the feasibility of physiological signals such as Galvanic Skin Response (GSR) and Blood Volume Pulse (BVP) as indicators for user trust in predictive decision making. A user study found that the presentation of influences of training data points significantly increases the user trust in predictions, but only for training data points with higher influence values under the high model performance condition, where users can justify their actions with more similar facts to the testing data point. The physiological signal analysis showed that GSR and BVP features correlate to user trust under different influence and model performance conditions. These findings suggest that physiological indicators can be integrated into the user interface of AI applications to automatically communicate user trust variations in predictive decision making

Cardiovascular Biomarkers’ Inherent Timescales in Mental Workload Assessment During Simulated Air Traffic Control Tasks

One central topic in ergonomics and human-factors research is the assessment of mental workload. Heart rate and heart rate variability are common for registering mental workload. However, a major problem of workload assessment is the dissociation among different workload measures. One potential reason could be the disregard of their inherent timescales and the interrelation between participants’ individual differences and timescales. The aim of our study was to determine if different cardiovascular biomarkers exhibit different timescales. We focused on air traffic controller and investigated biomarkers’ ability to distinguish between conditions with different load levels connected to prior work experience and different time slots. During an interactive real-time simulation, we varied the load situations with two independent variables: the traffic volume and the occurrence of a priority-flight request. Dependent variables for registering mental workload were the heart rate and heart rate variability from two time slots. Our results show that all cardiovascular biomarkers were sensitive to workload differences with different inherent timescales. The heart rate responded sooner than the heart rate variability features from the frequency domain and it was most indicative during the time slot immediately after the priority-flight request. The heart rate variability parameters from the frequency domain responded with latency and were most indicative during the subsequent time slot. Furthermore, by consideration of biomarkers’ inherent timescales, we were able to assess a significant effect of work experience on heart rate and mid/high frequency-band ratio of the heart rate variability. Results indicated that different cardiovascular biomarkers reveal different inherent timescales.Bundesanstalt für Arbeitsschutz und Arbeitsmedizin http://dx.doi.org/10.13039/501100006522Bundesanstalt für Arbeitsschutz und Arbeitsmedizin (BAuA) (4229)Peer Reviewe

Embedded system for real-time digital processing of medical Ultrasound Doppler signals

Ultrasound (US) Doppler systems are routinely used for the diagnosis of cardiovascular diseases. Depending on the application, either single tone bursts or more complex waveforms are periodically transmitted throughout a piezoelectric transducer towards the region of interest. Extraction of Doppler information from echoes backscattered from moving blood cells typically involves coherent demodulation and matched filtering of the received signal, followed by a suitable processing module. In this paper, we present an embedded Doppler US system which has been designed as open research platform, programmable according to a variety of strategies in both transmission and reception. By suitably sharing the processing tasks between a state-of-the-art FGPA and a DSP, the system can be used in several medical US applications. As reference examples, the detection of microemboli in cerebral circulation and the measurement of wall _distension_ in carotid arteries are finally presented

Dopamine Transporters in Striatum Correlate with Deactivation in the Default Mode Network during Visuospatial Attention

BACKGROUND:Dopamine and dopamine transporters (DAT, which regulate extracellular dopamine in the brain) are implicated in the modulation of attention but their specific roles are not well understood. Here we hypothesized that dopamine modulates attention by facilitation of brain deactivation in the default mode network (DMN). Thus, higher striatal DAT levels, which would result in an enhanced clearance of dopamine and hence weaker dopamine signals, would be associated to lower deactivation in the DMN during an attention task. METHODOLOGY/PRINCIPAL FINDINGS:For this purpose we assessed the relationship between DAT in striatum (measured with positron emission tomography and [(11)C]cocaine used as DAT radiotracer) and brain activation and deactivation during a parametric visual attention task (measured with blood oxygenation level dependent functional magnetic resonance imaging) in healthy controls. We show that DAT availability in caudate and putamen had a negative correlation with deactivation in ventral parietal regions of the DMN (precuneus, BA 7) and a positive correlation with deactivation in a small region in the ventral anterior cingulate gyrus (BA 24/32). With increasing attentional load, DAT in caudate showed a negative correlation with load-related deactivation increases in precuneus. CONCLUSIONS/SIGNIFICANCE:These findings provide evidence that dopamine transporters modulate neural activity in the DMN and anterior cingulate gyrus during visuospatial attention. Our findings suggest that dopamine modulates attention in part by regulating neuronal activity in posterior parietal cortex including precuneus (region involved in alertness) and cingulate gyrus (region deactivated in proportion to emotional interference). These findings suggest that the beneficial effects of stimulant medications (increase dopamine by blocking DAT) in inattention reflect in part their ability to facilitate the deactivation of the DMN

Characterisation of cardiac structure and function in late adolescence and modification by adiposity and other cardiovascular risk factors

Cardiovascular disease remains one of the leading causes of death worldwide. However, a large proportion of research in the field focuses primarily on middle- to old- age, by which time much damage to the heart and vascular system has been incurred. The rationale for this research was to gain a clearer picture of cardiovascular health in late adolescence, prior to the onset of adulthood. In this thesis I characterise the cardiac structure and function of individuals from the ALSPAC cohort (average age 17.7 years) through analysing M-Mode, two dimensional and Doppler echocardiographic measures and haemodynamic, biochemical and anthropometric measures. Adiposity, sex and genetic predisposition are considered as key exposures which impact a range of cardiovascular outcomes. I consider the relationships of fat mass and lean mass with cardiovascular outcomes and the ways in which left ventricular mass indexation is affected by adiposity, lean mass, height and body surface area. I then discuss the roles which particular haemodynamic and biochemical biomarkers have in mediating associations between fat mass and left ventricular structural and functional outcomes. Finally I consider the influence which genes associated with body mass index have on key cardiovascular measures, including cardiac structural and functional measures. Adiposity has a direct and detrimental effect on cardiovascular health. My findings provide insights into the way in which adiposity affects the development of an adverse cardiometabolic phenotype from a comparatively young age and also have interesting implications for future research. Furthermore, they serve as another important reminder of the need for adiposity to be monitored throughout the life course

The anthropometric, environmental and genetic determinants of right ventricular structure and function

BACKGROUND Measures of right ventricular (RV) structure and function have significant prognostic value. The right ventricle is currently assessed by global measures, or point surrogates, which are insensitive to regional and directional changes. We aim to create a high-resolution three-dimensional RV model to improve understanding of its structural and functional determinants. These may be particularly of interest in pulmonary hypertension (PH), a condition in which RV function and outcome are strongly linked. PURPOSE To investigate the feasibility and additional benefit of applying three-dimensional phenotyping and contemporary statistical and genetic approaches to large patient populations. METHODS Healthy subjects and incident PH patients were prospectively recruited. Using a semi-automated atlas-based segmentation algorithm, 3D models characterising RV wall position and displacement were developed, validated and compared with anthropometric, physiological and genetic influences. Statistical techniques were adapted from other high-dimensional approaches to deal with the problems of multiple testing, contiguity, sparsity and computational burden. RESULTS 1527 healthy subjects successfully completed high-resolution 3D CMR and automated segmentation. Of these, 927 subjects underwent next-generation sequencing of the sarcomeric gene titin and 947 subjects completed genotyping of common variants for genome-wide association study. 405 incident PH patients were recruited, of whom 256 completed phenotyping. 3D modelling demonstrated significant reductions in sample size compared to two-dimensional approaches. 3D analysis demonstrated that RV basal-freewall function reflects global functional changes most accurately and that a similar region in PH patients provides stronger survival prediction than all anthropometric, haemodynamic and functional markers. Vascular stiffness, titin truncating variants and common variants may also contribute to changes in RV structure and function. CONCLUSIONS High-resolution phenotyping coupled with computational analysis methods can improve insights into the determinants of RV structure and function in both healthy subjects and PH patients. Large, population-based approaches offer physiological insights relevant to clinical care in selected patient groups.Open Acces

Classifying User Predilections using Naïve Bayes Classifier (NBC) and Jaccard Similarity for Service Recommender System in Big Data Applications

Service recommender systems have been shown as valuable tools for providing appropriate recommendations to users. The main objective is to identify a system that will classify the user reviews using effective methods and provide personalized recommendations to the users. The proposed architecture will present the different ratings and rankings of services to different users by considering diverse users' preferences, and therefore it will meet users' personalized requirements. The data classification can be achieved through analysing the user review as positive or negative using Naive Bayes classifier (NBC) in large-scale datasets and Jaccard Similarity and MinHash used to compute the similarity and provide the recommendation to user

Developing and Validating Open Source Tools for Advanced Neuroimaging Research

Almost all scientific research relies on software. This is particularly true for research that uses neuroimaging technologies, such as functional magnetic resonance imaging (fMRI). These technologies generate massive amounts of data per participant, which must be processed and analyzed using specialized software. A large portion of these tools are developed by teams of researchers, rather than trained software developers. In this kind of ecosystem, where the majority of software creators are scientists, rather than trained programmers, it becomes more important than ever to rely on community-based development, which may explain why most of this software is open source. It is in the development of this kind of research-oriented, open source software that I have focused much of my graduate training, as is reflected in this dissertation. One software package I have helped to develop and maintain is tedana, a Python library for denoising multi-echo fMRI data. In chapter 2, I describe this library in a short, published software paper. Another library I maintain as the primary developer is NiMARE, a Python library for performing neuroimaging meta-analyses and derivative analyses, such as automated annotation and functional decoding. In chapter 3, I present NiMARE in a hybrid software paper with embedded tutorial code exhibiting the functionality of the library. This paper is currently hosted as a Jupyter book that combines narrative content and code snippets that can be executed online. In addition to research software development, I have focused my graduate work on performing reproducible, open fMRI research. To that end, chapter 4 is a repli- cation and extension of a recent paper on multi-echo fMRI denoising methods Power et al. (2018a). This replication was organized as a registered report, in which the introduction and methods were submitted for peer review before the analyses were performed. Finally, chapter 5 is a conclusion to the dissertation, in which I reflect on the work I have done and the skills I have developed throughout my training