Journal of medical Internet research
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J. Med. Internet Res. · Sep 2020
Artificial Intelligence and Its Effect on Dermatologists' Accuracy in Dermoscopic Melanoma Image Classification: Web-Based Survey Study.
Early detection of melanoma can be lifesaving but this remains a challenge. Recent diagnostic studies have revealed the superiority of artificial intelligence (AI) in classifying dermoscopic images of melanoma and nevi, concluding that these algorithms should assist a dermatologist's diagnoses. ⋯ The findings of our study show that AI support can improve the overall accuracy of the dermatologists in the dichotomous image-based discrimination between melanoma and nevus. This supports the argument for AI-based tools to aid clinicians in skin lesion classification and provides a rationale for studies of such classifiers in real-life settings, wherein clinicians can integrate additional information such as patient age and medical history into their decisions.
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J. Med. Internet Res. · Sep 2020
Association of Socioeconomic Changes due to the COVID-19 Pandemic With Health Outcomes in Patients With Skin Diseases: Cross-Sectional Survey Study.
The outbreak of COVID-19 has profoundly influenced people's lifestyles; these impacts have varied across subgroups of people. The pandemic-related impacts on the health outcomes of people with dermatological conditions are unknown. ⋯ Isolation, income loss, and unemployment are associated with impaired health-related quality of life in patients with skin diseases during the COVID-19 pandemic.
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J. Med. Internet Res. · Sep 2020
Excessive Media Consumption About COVID-19 is Associated With Increased State Anxiety: Outcomes of a Large Online Survey in Russia.
The COVID-19 pandemic has potentially had a negative impact on the mental health and well-being of individuals and families. Anxiety levels and risk factors within particular populations are poorly described. ⋯ Among Russian respondents from multiple social media platforms, there was evidence of higher levels of state anxiety associated with recent job loss and increased news consumption, as well as lower than expected trust in government agencies. These findings can help inform the development of key public health messages to help reduce anxiety and raise perceived trust in governmental response to this current national emergency. Using a similar methodology, comparative surveys are ongoing in other national populations.
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J. Med. Internet Res. · Sep 2020
Observational StudyExcess Patient Visits for Cough and Pulmonary Disease at a Large US Health System in the Months Prior to the COVID-19 Pandemic: Time-Series Analysis.
Accurately assessing the regional activity of diseases such as COVID-19 is important in guiding public health interventions. Leveraging electronic health records (EHRs) to monitor outpatient clinical encounters may lead to the identification of emerging outbreaks. ⋯ A significantly higher number of patients with respiratory complaints and diseases starting in late December 2019 and continuing through February 2020 suggests community spread of SARS-CoV-2 prior to established clinical awareness and testing capabilities. This provides a case example of how health system analytics combined with EHR data can provide powerful and agile tools for identifying when future trends in patient populations are outside of the expected ranges.
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J. Med. Internet Res. · Sep 2020
Association Between Generalized Anxiety Disorder Scores and Online Activity Among US Adults During the COVID-19 Pandemic: Cross-Sectional Analysis.
Evidence from past pandemics suggests that fear, uncertainty, and loss of control during large-scale public health crises may lead to increased pandemic-related information seeking, particularly among persons predisposed to high anxiety. In such groups, a greater consumption of information pertaining to the COVID-19 pandemic may increase anxiety. ⋯ Results from this study indicate that limiting pandemic-related online information seeking may aid anxiety management in our study population.