Towards a Standard of Modelling Annotations in the E-Health Domain

A large number of annotation systems in e-health domain have been implemented in the literature. Several factors distinguish these systems from one another. In fact, each of these systems is based on a separate paradigm, resulting in a disorganized and unstructured vision. As part of our research, we attempted to categorize them based on the functionalities provided by each system, and we also proposed a model of annotations that integrates both the health professional and the patient in the process of annotating the medical file.

Heat Illness Prevention in the Outdoor Workplace

In the construction industry a large amount of work is completed outdoors where the sun may expose or heat up rooms that can affect employees while working. This research will recognize how companies combat with heat illness and heat prevention methods to keep employees healthy and safe while working in high temperatures. Each year in the United States thousands of employees fall ill to heat related illnesses, stem from heat rash to heat stroke, which can be fatal, if not treated properly. Research will examine what standards are required by the Occupational Safety & Health Administration (OSHA) and how many participants companies currently abide by those standards. Every day that employees who work outdoors or in high temperature facilities go without proper training and education about heat stress, the number of cases will rise and more will become ill to heat related complications. This study will give prevention methods to help keep American workers safe.

Clinical and Social Determinants to Improve Dod/Veteran Well Being: The Service Member Veteran Risk Profile

This paper introduces the Service member Veteran Risk Profile (SVRP), a mathematical process/solution to quantitatively represent transitioning Service member (TSM) and/or Veteran quality of life risks by integrating clinical and social determinant data into an individual risk profile. The SVRP creates, for the first time, a mechanism for the Department of Defense (DoD) and Department of Veterans Affairs (VA) to holistically represent the challenges of military members transitioning into civilian life that can lead to negative outcomes and proactively identify transitioning Service members and Veterans at risk. More importantly, the SVRP supports clinical and non-clinical modalities to reduce the negative impacts of transition and beyond for TSM and Veterans. Lastly, the SVRP can be displayed through user-friendly visualizations so DoD/VA policymakers and decision-makers can make more informed policy and resource decisions to improve TSM/Veteran overall quality of life.

Detecting Fatigue in the Workplace

This paper evaluates current case studies on how companies within the United States detect fatigue in the workplace, and how it is addressed through training. Workplace fatigue is one of the highest risks for safety sensitive positions and presents an imminent danger to employees and their coworkers. Corporations have developed ways to observe for fatigue, lack of training and acknowledgement many cases of workplace fatigue go under the radar and can eventually lead to an incident. Why is there such an influx of fatigue related incidents, and why are companies not better at recognizing the signs and symptoms of workplace fatigue? The intention is to suggest and recommend safe work practices for workers to combat fatigue before, during and after fatigue has set in. Corrective measures would include proper training, a well-balanced diet, and proper rest between each shift. This paper will also review sleep/wake cycles that moderate the human body and the way we mitigate workplace fatigue.

Language Characteristics Supporting Early Alzheimer's Diagnosis through Machine Learning - A Literature Review

Alzheimer's dementia (AD) is the most common incurable neurodegenerative disease worldwide. Apart from memory loss, AD leads to speech disorders. Timely diagnosis is crucial to halt the progression of the disease. However, current diagnostic procedures are costly, invasive, and distressing. Early-stage AD manifests itself in speech disorders, which implies examining those. Machine Learning (ML) represents a promising instrument in this context. Nevertheless, no genuine consensus on the language characteristics to be analyzed exists. To counteract this deficit and provide topic-related researchers with a better basis for decision-making, we present, based on a literature review, favourable speech characteristics for the appliance toward AD detection via ML. Research trends to apply spontaneous speech, gained from image descriptions, as analysis basis, and points out that the combined use of acoustic, linguistic, and demographic features positively influences recognition accuracy. In total, we have identified 97 overarching acoustic, linguistic and demographic features.

The Correlation between HPV Vaccination Rate and Income Inequality

According to the 2018 National Immunization Survey - Teen (NIS-Teen), the human papillomavirus (HPV) vaccination coverage in the U.S. increased from 48.6% to 51.1%.[1] Certain factors contribute to disparity between teenagers receiving HPV vaccination.[1]The factors are geography, race, gender, education level, household income, and etc. Within these factors, household income and income inequality were chosen to be the focus of this study. The relationship between HPV vaccination coverage in the U.S., the household income of interviewed individuals, and the Gini index in the U.S. have been studied in RStudio [2]. By merging the NIS-Teen data of vaccination rate and Gini index data in RStudio, charts and graphs are formed to illustrate the relationship between HPV vaccination rate and income inequality. There seem to be limited correlations between vaccination rate and Gini index, but unexpected connections between vaccination rate and household income have been found.

Influenza Awareness in the Workplace

The United States has been actively researching Western medicine and disease prevention. Influenza is a common viral infection that it is widely known can be fatal. Nonetheless, complacency has become common. Not all workplaces and community training centers outside medical facilities properly train employees on the hazards associated with contracting influenza. However, standard training procedures and a wide variety of resources are used to disseminate awareness of seasonal influenza (flu). The United States Centers for Disease Control (CDC) publish morbidity and mortality rates and alert the public to any pandemics. Its estimates of influenza cases are delivered in three age categories: <19 years, 19–64 years, and ≥65 years (CDC, 2010). This study aims to incorporate prevention methods that have not been used to help protect American workers.

Organizational Factors in Determining Data Quality Produced from Health Management Information Systems in Low- And Middle-income Countries: A Systematic Review

The Health Management Information System (HMIS) is an essential core component in framing the national health system. To operate six core components synchronically and to manage them successfully inside the health system, HMIS and communication are also placed centrally. However, the unworthy problems of HMIS data have been significantly affected by several characteristics. Among these characteristics, the organizational factors need to be considered as important issues. This systematic review aims to examine what organizational factors are determining the HMIS data quality in LMICs after 2005. Two independent reviewers selected 38 eligible primary published papers from 22 LMICs through three popular online sources: MEDLINE and PubMed, HINARI, and Google and Google Scholar. This finding mainly highlighted that weak organizational structuring and processing, less organizational learning development regarding HMIS, unavailability of HMIS resources, poor governance, and political issues impacted the HMIS data quality in LMICs.