Prevalence, Mechanisms, and Implications of Gastrointestinal Symptoms in COVID-19

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. The infection started as an outbreak of pneumonia-like symptoms in Wuhan, China. Within a few weeks, it spread across the entire globe resulting in millions of cases and thousands of deaths. While respiratory symptoms and complications are well-defined and can be severe, non-respiratory symptoms of COVID-19 are increasingly being recognized. Gastrointestinal manifestations such as nausea, vomiting, diarrhea, and abdominal pain have been added to the list of common COVID-19 symptoms. Their prevalence has been increasing, probably due to increased recognition and experience with the pandemic. Furthermore, diarrhea and stool testing may change prevalence and transmission rates due to suspicion for fecal-oral transmission of the COVID-19. Due to this risk, various countries have started testing wastewater and sewage systems to examine its role in the spread of SARS-CoV-2 among communities. In this review article, we describe the common gastrointestinal manifestations in COVID-19, their prevalence based upon the current literature, and highlight the importance of early recognition and prompt attention. We also note the role of fecal-oral transmission. Furthermore, the mechanisms of these symptoms, the role of medications, and potential contributing factors are also elaborated

Developing a Smart Home Technology Innovation for People With Physical and Mental Health Problems: Considerations and Recommendations

Smart home technologies present an unprecedented opportunity to improve health and health care by providing greater communication and connectivity with services and care providers and by supporting the daily activities of people managing both mental and physical health problems. Based on our experience from conducting smart technology health studies, including a smart home intervention, we provide guidance on developing and implementing such interventions. First, we describe the need for an overarching principle of security and privacy that must be attended to in all aspects of such a project. We then describe 4 key steps in developing a successful smart home innovation for people with mental and physical health conditions. These include (1) setting up the digital infrastructure, (2) ensuring the components of the system communicate, (3) ensuring that the system is designed for the intended population, and (4) engaging stakeholders. Recommendations on how to approach each of these steps are provided along with suggested literature that addresses additional considerations, guidelines, and equipment selection in more depth

Fine-Grained Filtering to Provide Access Control for Data Providing Services within Collaborative Environments

A data providing service (DPS) in service-oriented architecture is tasked only with the retrieval of data that are annotated over a domain ontology. One particular motivating application of DPSs is their use within collaborative environments. An important characteristic for the enterprises of such a collaborative environment is the ability to employ data sharing with one another. A major concern in this situation is the protection of each enterprise\u27s privacy while still permitting data sharing. One potential solution is to provide filtered data through access control. This work describes how to implement access control through fine-grained filtering of DPS response messages; it is accomplished using a filtering ontology and relations between the domain ontology of DPS and the proposed filtering ontology. Therefore, enterprises can write enterprise-specific access control policies referencing a common filtering ontology defined within a collaborative environment, enabling access control-based data sharing within the environment. This work additionally illustrates the implementation of our general solution to data providing web services, interpreted by an eXtensible Access Control Markup Language-based access control framework. The implementation is further evaluated in a case study of real world data, provided by a health research institute in London, Canada

A Smart Technology Intervention in the Homes of People with Mental Illness and Physical Comorbidities

Appropriate support in the home may not be readily available for people living in the community with mental illness and physical comorbidities. This mixed-method study evaluated a smart home technology intervention for individuals within this population as well as providing health care providers with health monitoring capabilities. The study recruited 13 participants who were offered a smartphone, a touchscreen monitor, and health devices, including smartwatches, weigh scales, and automated medication dispensers. Healthcare providers were able to track health device data, which were synchronized with the Lawson Integrated DataBase. Participants completed interviews at baseline as well as at 6-month and 12-month follow-ups. Focus groups with participants and care providers were conducted separately at 6-month and 12-month time points. As the sample size was too small for meaningful statistical inference, only descriptive statistics were presented. However, the qualitative analyses revealed improvements in physical and mental health, as well as enhanced communication with care providers and friends/family. Technical difficulties and considerations are addressed. Ethics analyses revealed advancement in equity and fairness, while policy analyses revealed plentiful opportunities for informing policymakers. The economic costs are also discussed. Further studies and technological interventions are recommended to explore and expand upon in-home technologies that can be easily implemented into the living environment

Scope of Artificial Intelligence in Screening and Diagnosis of Colorectal Cancer

Globally, colorectal cancer is the third most diagnosed malignancy. It causes significant mortality and morbidity, which can be reduced by early diagnosis with an effective screening test. Integrating artificial intelligence (AI) and computer-aided detection (CAD) with screening methods has shown promising colorectal cancer screening results. AI could provide a "second look" for endoscopists to decrease the rate of missed polyps during a colonoscopy. It can also improve detection and characterization of polyps by integration with colonoscopy and various advanced endoscopic modalities such as magnifying narrow-band imaging, endocytoscopy, confocal endomicroscopy, laser-induced fluorescence spectroscopy, and magnifying chromoendoscopy. This descriptive review discusses various AI and CAD applications in colorectal cancer screening, polyp detection, and characterization