Transfer Learning for Human & AI

The significance of social media has increased manifold in the past fewdecades as it helps people from even the most remote corners of the world to stay connected . With the advent of technology, digital media has become morerelevant and widely used than ever before .…

Study investigates the performance of a deep learning-based model for lung segmentation from CT images for normaland COVID-19 patients . Chest CT images and corresponding lung masks of 1200 confirmed COV-19 cases were used for training a residual neural network .…

Sound-based COVID-19 detection studies have shown great promise toachieve scalable and prompt digital pre-screening . However, there are still twounsolved issues hindering the practice . Data collected for modeltraining are often imbalanced, with a considerably smaller proportion of userstested positive, making it harder to learn representative and robust features .…

During the Covid-19 pandemic, most governments across the world imposedpolicies like lock-down of public spaces and restrictions on people’s movement . Such policies have grave social and economic costs, and so it is important topre-assess their impacts . In this work we aim to visualize the dynamics of thepandemic in a city under different intervention policies, by simulating the behavior of the residents .…

The unscented transform uses a weighted set of samples called sigma points to topropagate the means and covariances of nonlinear transformations of randomvariables . For correlated random vectors, the GenUT can accurately approximate the mean and covariance . The GenUT uses the same order of calculations that guarantee third-order accuracy, which makes it applicable to a wide variety of applications, such as the modeling of the coronavirus (SARS-CoV-2), causing COVID-19 .…

Making a trade-off between economic recovery and infection control is a major challenge confronting many hard-hit counties . Understanding the transmission process and quantifying thecosts of local policies are essential to tackling this challenge . We simulate the epidemicspread with a time-varying contagion model in ten large metropolitan counties in the United States .…

Gadolinium-based contrast agents (GBCAs) have been widely used to bettervisualize disease in brain magnetic resonance imaging (MRI) However, gadolinium deposition within the brain and body has raised safety concerns about the use of GBCAs . The development of novel approaches that candecrease or eliminate GBCA exposure while providing similar contrastinformation would be of significant use clinically .…

Non-negative matrix and tensor factorisations are a classical tool in machinelearning and data science . In applications such as imaging, datasets can often be regarded as distributions in a space with metric structure . We introduce a general mathematical framework for computing non-negative factorisations of matrices and tensors with respect to an optimal transport loss, and derive an efficient method for its solution using a convexdual formulation .…

Graphics Processing Units (GPUs) have been widely used to accelerate artificial intelligence, physics simulation, medical imaging, and informationvisualization applications . Daisen is a framework that supports data collection from GPU simulators and provides visualization of thesimulator-generated GPU execution traces . The open-sourced implementation of Daisen can be found atgitlab.com/akita/vis…

The number of end devices that use the last mile wireless connectivity isdramatically increasing with the rise of smart infrastructures . Toefficiently manage such massive wireless networks, more advanced and accurate monitoring and malfunction detection solutions are required . The best performing model based on recurrence plot transformation leads to up to 55% increase compared to the state of the art where classical machine learning techniques are used .…

Social media plays a pivotal role in disseminating news across the globe andacts as a platform for people to express their opinions on a variety of topics . Nearly 600 thousand vaccine-related tweets from the United States and India were analyzed for an overallunderstanding of the situation around the world for the time period of 8 months from June 2020 to January 2021 .…

In this chapter, we discuss applications of topological data analysis (TDA) to spatial systems . We briefly review the recently proposed level-setconstruction of filtered simplicial complexes . We then examine persistenthomology in two cases studies: street networks in Shanghai and hotspots ofCOVID-19 infections .…

This paper presents Out-of-Context Summarizer, a tool that takes arbitrarypublic news articles out of context by summarizing them to coherently fiteither a liberal- or conservative-leaning agenda . The tool suggests hashtag keywords to bolster the polarization of the summary, incase one is inclined to take it to Twitter, Parler or other platforms fortrolling .…

Twitter, prompted by the rapid spread of alternative narratives, startedactively warning users about the spread of COVID-19 misinformation . This formof soft moderation comes in two forms: as a warning cover before the Tweet isdisplayed to the user and a warning tag below the Tweet .…

Algorithmic fairness has emphasized the role of biased data in automated decision outcomes . We argue that choice of metric for modelcomparison can significantly bias model selection outcomes . Using a deep learning model trained on real-world medical imaging data, we verify our claim empirically .…

Strong water absorption nature and low noise tolerance lead to undesiredblurring and distortion of reconstructed terahertz images . MS3-Unet uses multi-scale branches to extract spatio-spectral features then processed by element-wise adaptive filters, and then fused to achieve high-quality image restoration .…

This work considers sequential edge-promoting Bayesian experimental design for (discretized) linear inverse problems, exemplified by X-ray tomography . The process of computing a total variation type reconstruction of the absorption inside the imaged body via lagged diffusivity iteration is interpreted in theBayesian framework .…

The majority of model-based learned image reconstruction methods in medical imaging have been limited to uniform domains such as pixelated images . If the underlying model is solved on nonuniform meshes, interpolation and embeddings are needed . This gives rise to the proposed iterative Graph ConvolutionalNewton’s Method (GCNM) The GCNM has strong generalizability to different domain shapes, out of distribution data as well as experimental data, from purely simulated training data .…

We propose a selective learning method using meta-learning and deepreinforcement learning for medical image interpretation in the setting of limited labeling resources . We believe that our method may be broadly applicable across medicalimaging settings where labels are expensive to acquire.…

Pandemics can bring a range of devastating consequences to public health and the world economy . Various public health control strategies have been proposed and tested against pandemic diseases (e.g.,COVID-19) We study two specific pandemic control models: the susceptible,exposed, infectious, recovered (SEIR) model with vaccination control; and theSEIR model with shield immunity control .…

Many techniques have been proposed for image reconstruction in medical imaging that aim to recover high-quality images especially from limited or corrupted measurements . Model-based reconstruction methods have beenparticularly popular (e.g., in magnetic resonance imaging and tomographicmodalities) and exploit models of the imaging system’s physics together withstatistical models of measurements, noise and often simple objectpriors .…

Compliance with public health measures, such as restrictions on movement and socialization, is paramount in limiting the spread of diseases such as thesevere acute respiratory syndrome coronavirus 2 (also referred to as COVID-19) In this work, we examine the usefulness of videosharing on social media as a proxy of the amount of time Internet users spend at home .…

Governments, Healthcare, and Private Organizations in the global scale have been using digital tracking to keep COVID-19 outbreaks under control . Although this method could limit pandemic contagion, it raises significant concerns about user privacy . We found that three regulations (GDPR, COPPA, and CCPA) analyzed defined mobile location data as private information, and two (T-Mobile US, Boost Mobile) of the fiveCSPs that were analyzed did not comply with the COPPA regulation .…

TrackYourHealth (TYH) is a highly configurable, generic, and modular mobile data collection and EMA platform . It enabled us to develop and release two mobile multi-platform applications related to COVID-19 in just afew weeks . We present TYH and highlight specific challenges researchers and developers of similar apps may also face, especially when developing apps related to the medical field .…

Wordassociation thematic analysis (WATA) was applied to English-languagevaccine-related tweets from eight countries gathered between 5 December 2020and 21 March 2021 . The method was able to quickly identify multipleinternational differences . Ireland seemed to be the only country in which university presidents were widelytweeted about in vaccine discussions .…

A key challenge in responding to public health crises such as COVID-19 is the difficulty of predicting the results of feedback interconnections between the disease and society . We study the game-theoretic equilibria that emerge from this setup when the population is composed of either selfish or altruistic individuals .…

Wireless contact tracing has emerged as an important tool for managing theCOVID-19 pandemic and relies on continuous broadcasting of a person’s presence using Bluetooth Low Energy beacons . The limitation of current contact tracingsystems is in that a reception of a single beacon is sufficient to reveal the user’s identity, potentially exposing users to malicious trackers installed along theroads, passageways, and other infrastructure .…

Phishing attack traffic in March and April 2020 skyrocketed upto 220\% of its pre-COVID-19 rate, far exceeding typical seasonal spikes . Attackers exploited victims’ uncertainty and fear related to the pandemic through a variety of highly targeted scams, including emerging scam types against which current defenses are not sufficient as well as traditional phishing which outpaced the ecosystem’s collective response .…

Report presents analysis of #hashtags used by Italian CulturalHeritage institutions to promote and communicate cultural content during theCOVID-19 lock-down period in Italy . Results show that on one side Italian institutions have been proactive in adapting to the pandemic scenario and on the other side users’ reacted very positively increasing their participation in the proposed activities .…

This study aims to develop an end-to-end natural languageprocessing pipeline for triage and diagnosis of COVID-19 from patient-authored social media posts . The text processing pipeline firstextracts symptoms and related concepts such as severity, duration,negations, and body parts from patients posts using conditional random fields .…

In clinical practice, regions of interest in medical imaging often need to beidentified through a process of precise image segmentation . We introduce a novel deep neural network architecture that exploits theinherent spatial coherence of anatomical structures and is well equipped to capture long-range spatial dependencies in the segmented pixel/voxel space .…

Age prediction based on Magnetic Resonance Imaging (MRI) data of the brain is a biomarker to quantify the progress of brain diseases and aging . Here we describe a 3DConvolutional Neural Network (CNN) based on the ResNet architecture beingtrained on raw, non-registered T 1 -weighted MRI data of N=10,691 samples from the German National Cohort .…

We established a Spatio-Temporal Neural Network, namely STNN, to forecast thespread of the coronavirus COVID-19 outbreak worldwide in 2020 . The basicstructure of STNN is similar to the Recurrent Neural Network (RNN) It incorporates with not only temporal data but also spatial features .…

In this paper, we study the moral framing of political content on Twitter . We examine differences in moral framing in two datasets: (i)tweets from US-based politicians annotated with political affiliation and (ii) COVID-19 related tweets in German from leaders of the five major Austrian political parties .…

The proposed approach outperformsmonocular and conventional techniques for dealing with 4D imagery . It yields more accurate odometry and depth maps and delivers these with metric scale . We anticipate our technique to generalise to a broad class of LF and sparse LFcameras, and to enable unsupervised recalibration for coping with shifts incamera behaviour over the lifetime of a robot.…

During 2020, social media chatter has been largely dominated by the COVID-19pandemic . Right-leaning users, we find, are noticeably more vocal and active inthe production and consumption of information . Our analysis also showsthat most of the highly influential users are partisan, which may contribute to further polarization.…

We analyzed Medical Subject Headings (MeSH) from 21.6 million researcharticles indexed by PubMed to map this vast space of entities and theirrelations . We provide insights into the origins and future of biomedicalconvergence . We show convergence to be increasing in prominence but with recent saturation .…

Material microscopy is experiencing an explosion of published imaging data . The standard publication format is not conducive to large-scale data aggregation oranalysis, hindering data sharing and reuse . We highlight the methodology behind the construction of the EXSCLAIM! Python toolkit for the automatic EXtraction,Separation, and Caption-based natural Language Annotation of IMages from scientific literature.…

TextEssence is an interactive system designed to enable comparative analysis of corpora using embeddings . The system includes visual,neighbor-based, and similarity-based modes of embedding analysis in alightweight, web-based interface . A case study on COVID-19 scientific literature illustrates the utility of the system .…

In this paper we describe our efforts to make a bidirectional CongoleseSwahili (SWC) to French (FRA) neural machine translation system . We recorded improvementsof up to 2.4 and 3.5 BLEU points in the SWC-FRA and FRA-SWC directions, respectively . We performed human evaluations to assess the usability of our models in a COVID-domain chatbot that operates in the Democratic Republic ofCongo (DRC) We make our models, datasets containing up to 1million sentences, our development pipeline, and a translator web-app available for public use .…

Since the outbreak of the novel coronavirus, COVID-19, there has been increased interest in the use of digital contact tracing as a means of stoppingchains of viral transmission, provoking alarm from privacy advocates . We provide a comprehensive survey of the evolvingecosystem of .…

Digital contact tracing has been deployed as a public health intervention to suppress the spread of COVID-19 in many jurisdictions . Mostgovernments have struggled with low uptake and participation rates, limiting the effectiveness of the tool . This paper characterises a number of systems developed around the world, comparing the uptake rates for systems with different technology, data architectures, and mandates .…

The risk for severe illness and mortality from COVID-19 significantly increases with age . Age-stratified modeling is key to study how to reduce hospitalizations and mortality . The elderly should be prioritized only when reproduction number R0 is relatively high .…

Motion artifacts are a common occurrence in the Magnetic Resonance Imaging(MRI) exam . Motion artifacts in MRI have a complex nature and it is related to the k-space sampling scheme . Cartesian samplers, on the otherhand, are the best in terms of deep learning motion detection because they can better reflect motion .…

Current BA estimation approaches are restricted to skeletal images or rely on non-imaging modalities that yield a whole-body BA assessment . Various organ systems may exhibit different aging characteristics due to lifestyle and genetic factors . In thisinitial study, we propose a new framework for organ-specific BA estimation using 3D magnetic resonance image (MRI) scans .…

Finding summaries from an orthopantomogram, or a dental panoramic radiograph, have significant potential to improve patient communication and to speed up clinical judgments . A finding summary has to not only find teeth in the imaging study but alsolabel the teeth with several types of treatments .…

The recent global outbreak of covid-19 is affecting many countries around the world . Due to the growing number of newly infected individuals and the health-care system bottlenecks, it will be useful to predict the upcoming number of patients . The study aims to efficiently forecast the is used to estimate new cases, number of deaths, and number of recovered patients in Iran for 180 days .…

Coronavirus disease 2019 (COVID-19) has been the main agenda of the whole world, since it came into sight in December 2019 as it has significantly affected the world economy and healthcare system . The proposed approach has achieved an outstanding detection performance with both sensitivity and specificity values above 99% .…

In response to the COVID-19 pandemic, Bluetooth-based contact tracing has been deployed in many countries . We propose a privacy-preserving exposure notification under situations where none of the middle entities can be trusted . We believe that it can beachieved with small changes to the existing mechanism: random numbers aregenerated on the application side instead of the OS .…

In this paper, we introduce two remote extended reality (XR) research methodsthat can overcome the limitations of lab-based controlled experiments, especially during the COVID-19 pandemic . We used a boxstacking task including three interaction modalities – two multimodalgaze-based interactions as well as a unimodal hand-based interaction .…