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Monitoring COVID-19 pandemic through the lens of social media using natural language processing and machine learning
ConclusionThe findings in our study show that the use of Reddit data to monitor COVID-19 pandemic in North Carolina (NC) was effective. The study shows the utility of NLP methods (e.g. cosine similarity, Latent Dirichlet Allocation (LDA) topic modeling, custom NER and BERT-based sentence clustering) in discovering the change of the public's concerns/behaviors over the course of COVID-19 pandemic in NC using Reddit data. Moreover, the results show that social media data can be utilized to surveil the epidemic situation in a specific community. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - June 25, 2021 Category: Information Technology Source Type: research

New bag of deep visual words based features to classify chest x-ray images for COVID-19 diagnosis
ConclusionOur method could be a very useful tool for the quick diagnosis of COVID-19 patients on a large scale. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - June 18, 2021 Category: Information Technology Source Type: research

Guest Editorial: Special issue on “Artificial Intelligence in Health Informatics”
(Source: Health Information Science and Systems)
Source: Health Information Science and Systems - June 9, 2021 Category: Information Technology Source Type: research

Who determines United States Healthcare out-of-pocket costs? Factor ranking and selection using ensemble learning
ConclusionOur results indicate a set of factors which best explain the OOP costs behavior based on a purely data-driven solution. These findings contribute to the discussions regarding demand-side needs for containing rapidly rising OOP costs. Instead of estimating the impact of a single factor on OOP costs, our proposed method allows for the selection of arbitrary-sized factors to best explain OOP costs. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - June 7, 2021 Category: Information Technology Source Type: research

Fast prototyping of a local fuzzy search system for decision support and retraining of hospital staff during pandemic
ConclusionsThis project points to the possibility of rapid prototyping and effective usage of ”patient-like-mine” search systems at the time of a pandemic caused by a poorly known pathogen. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - May 11, 2021 Category: Information Technology Source Type: research

Computer-aided diagnosis of hepatocellular carcinoma fusing imaging and structured health data
ConclusionThe classification performance achieved with the multimodal deep learning algorithm is higher than human specialists diagnostic performance using only CT for diagnosis. Even though the results are promising, the multimodal deep learning architecture used for hepatocellular carcinoma prediction needs more training and test processes using different datasets before the use of the proposed algorithm by physicians in real healthcare routines. The additional training aims to confirm the classification performance achieved and enhance the model ’s robustness. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - May 4, 2021 Category: Information Technology Source Type: research

Physicians ’ and pharmacists’ use of My Health Record in the emergency department: results from a mixed-methods study
ConclusionParticipants reported My Health Record use in the emergency department delivers efficiencies for clinicians and has a heightened utility for complex patients, consistent with previous research conducted outside of the Australian setting. Barriers to use were revealed: outdated content, a lack of trust, a low perception of value, no patient record and multiple medical record systems. The participants in this study highlighted that training and awareness raising is needed in order to improve My Health Record use in the emergency department, a need stressed by physician ’s. Further observational research is requir...
Source: Health Information Science and Systems - April 16, 2021 Category: Information Technology Source Type: research

Contact tracing apps for the COVID-19 pandemic: a systematic literature review of challenges and future directions for neo-liberal societies
AbstractPurposeThe COVID-19 pandemic has spread with increased fatalities around the world and has become an international public health crisis. Public health authorities in many countries have introduced contact tracing apps to track and trace infected persons as part of measures to contain the spread of the Severe Acute Respiratory Syndrome-Coronavirus 2. However, there are major concerns about its efficacy and privacy which affects mass acceptance amongst a population. This systematic literature review encompasses the current challenges facing this technology and recommendations to address such challenges in the fight a...
Source: Health Information Science and Systems - April 13, 2021 Category: Information Technology Source Type: research

Detecting autism spectrum disorder using machine learning techniques
AbstractAutism Spectrum Disorder (ASD), which is a neuro development disorder, is often accompanied by sensory issues such an over sensitivity or under sensitivity to sounds and smells or touch. Although its main cause is genetics in nature, early detection and treatment can help to improve the conditions. In recent years, machine learning based intelligent diagnosis has been evolved to complement the traditional clinical methods which can be time consuming and expensive. The focus of this paper is to find out the most significant traits and automate the diagnosis process using available classification techniques for impro...
Source: Health Information Science and Systems - April 6, 2021 Category: Information Technology Source Type: research

Automatic breast tissue segmentation in MRIs with morphology snake and deep denoiser training via extended Stein ’s unbiased risk estimator
AbstractAccurate segmentation of the breast tissue is a significant challenge in the analysis of breast MR images, especially analysis of breast images with low contrast. Most of the existing methods for breast segmentation are semi-automatic and limited in their ability to achieve accurate results. This is because of difficulties in removing landmarks from noisy magnetic resonance images (MRI). Especially, when tumour is imaged for scanning, how to isolate the tumour region from chest will directly affect the accuracy for tumour to be detected. Due to low intensity levels and the close connection between breast and chest ...
Source: Health Information Science and Systems - April 5, 2021 Category: Information Technology Source Type: research

COVID-19 infection map generation and detection from chest X-ray images
This study proposes a novel method for the joint localization, severity grading, and detection of COVID-19 from CXR images by generating the so-calledinfection maps. To accomplish this, we have compiled the largest dataset with 119,316 CXR images including 2951 COVID-19 samples, where the annotation of the ground-truth segmentation masks is performed on CXRs by a novel collaborative human –machine approach. Furthermore, we publicly release the first CXR dataset with the ground-truth segmentation masks of the COVID-19 infected regions. A detailed set of experiments show that state-of-the-art segmentation networks can lear...
Source: Health Information Science and Systems - April 1, 2021 Category: Information Technology Source Type: research

Quantitative EEG in sports: performance level estimation of professional female soccer players
ConclusionConsequently, the results of the present study can provide information to help staff coaches to choose the best performing players, representing an alternative method for accurately selecting key players in the competitive sports community. (Source: Health Information Science and Systems)
Source: Health Information Science and Systems - March 26, 2021 Category: Information Technology Source Type: research

Crosstalk disrupts the production of motor imagery brain signals in brain –computer interfaces
AbstractBrain –computer interfaces (BCIs) target specific brain activity for neuropsychological rehabilitation, and also allow patients with motor disabilities to control mobility and communication devices. Motor imagery of single-handed actions is used in BCIs but many users cannot control the BCIs effectively , limiting applications in the health systems. Crosstalk is unintended brain activations that interfere with bimanual actions and could also occur during motor imagery. To test if crosstalk impaired BCI user performance, we recorded EEG in 46 participants while they imagined movements in four experi mental conditi...
Source: Health Information Science and Systems - March 13, 2021 Category: Information Technology Source Type: research

Source-specific contributions of particulate matter to asthma-related pediatric emergency department utilization
In this study, we estimated the contributions of sources of PM2.5 and examined their association with daily asthma hospital utilization in Cincinnati, Ohio, USA. We used a model-based clustering method to group days with similar source-specific contributions into six distinct clusters. Specifically, elevated PM2.5 concentrations occurring on days characterized by low coal combustion contributions showed a significantly reduced risk of hospital utilization for asthma (rate ratio: 0.86, 95% CI: [0.77, 0.95]) compared to other clusters. Reducing coal combustion contribution to PM2.5 levels could be an effective intervention f...
Source: Health Information Science and Systems - March 10, 2021 Category: Information Technology Source Type: research

Knowledge Graphs of Kawasaki Disease
AbstractKawasaki Disease is a vasculitis syndrome that is extremely harmful to children. Kawasaki Disease can cause severe symptoms of ischemic heart disease or develop into ischemic heart disease, leading to death in children. Researchers and clinicians need to analyze various knowledge and data resources to explore aspects of Kawasaki Disease. Knowledge Graphs have become an important AI approach to integrating various types of complex knowledge and data resources. In this paper, we present an approach for the construction of Knowledge Graphs of Kawasaki Disease. It integrates a wide range of knowledge resources related ...
Source: Health Information Science and Systems - February 27, 2021 Category: Information Technology Source Type: research