Background
Individuals with large followings can influence public opinions and behaviors, especially during a pandemic. In the early days of the pandemic, US president Donald J Trump has endorsed the ...use of unproven therapies. Subsequently, a death attributed to the wrongful ingestion of a chloroquine-containing compound occurred.
Objective
We investigated Donald J Trump’s speeches and Twitter posts, as well as Google searches and Amazon purchases, and television airtime for mentions of hydroxychloroquine, chloroquine, azithromycin, and remdesivir.
Methods
Twitter sourcing was catalogued with Factba.se, and analytics data, both past and present, were analyzed with Tweet Binder to assess average analytics data on key metrics. Donald J Trump’s time spent discussing unverified treatments on the United States’ 5 largest TV stations was catalogued with the Global Database of Events, Language, and Tone, and his speech transcripts were obtained from White House briefings. Google searches and shopping trends were analyzed with Google Trends. Amazon purchases were assessed using Helium 10 software.
Results
From March 1 to April 30, 2020, Donald J Trump made 11 tweets about unproven therapies and mentioned these therapies 65 times in White House briefings, especially touting hydroxychloroquine and chloroquine. These tweets had an impression reach of 300% above Donald J Trump’s average. Following these tweets, at least 2% of airtime on conservative networks for treatment modalities like azithromycin and continuous mentions of such treatments were observed on stations like Fox News. Google searches and purchases increased following his first press conference on March 19, 2020, and increased again following his tweets on March 21, 2020. The same is true for medications on Amazon, with purchases for medicine substitutes, such as hydroxychloroquine, increasing by 200%.
Conclusions
Individuals in positions of power can sway public purchasing, resulting in undesired effects when the individuals’ claims are unverified. Public health officials must work to dissuade the use of unproven treatments for COVID-19.
Background
Positive economic impact is a key decision factor in making the case for or against investing in an artificial intelligence (AI) solution in the health care industry. It is most relevant ...for the care provider and insurer as well as for the pharmaceutical and medical technology sector. Although the broad economic impact of digital health solutions in general has been assessed many times in literature and the benefit for patients and society has also been analyzed, the specific economic impact of AI in health care has been addressed only sporadically.
Objective
This study aimed to systematically review and summarize the cost-effectiveness studies dedicated to AI in health care and to assess whether they meet the established quality criteria.
Methods
In a first step, the quality criteria for economic impact studies were defined based on the established and adapted criteria schemes for cost impact assessments. In a second step, a systematic literature review based on qualitative and quantitative inclusion and exclusion criteria was conducted to identify relevant publications for an in-depth analysis of the economic impact assessment. In a final step, the quality of the identified economic impact studies was evaluated based on the defined quality criteria for cost-effectiveness studies.
Results
Very few publications have thoroughly addressed the economic impact assessment, and the economic assessment quality of the reviewed publications on AI shows severe methodological deficits. Only 6 out of 66 publications could be included in the second step of the analysis based on the inclusion criteria. Out of these 6 studies, none comprised a methodologically complete cost impact analysis. There are two areas for improvement in future studies. First, the initial investment and operational costs for the AI infrastructure and service need to be included. Second, alternatives to achieve similar impact must be evaluated to provide a comprehensive comparison.
Conclusions
This systematic literature analysis proved that the existing impact assessments show methodological deficits and that upcoming evaluations require more comprehensive economic analyses to enable economic decisions for or against implementing AI technology in health care.
Trial Registration
Precision medicine is the personalization of medicine to suit a specific group of people or even an individual patient, based on genetic or molecular profiling. This can be done using genomic, ...transcriptomic, epigenomic or proteomic information. Personalized medicine holds great promise, especially in cancer therapy and control, where precision oncology would allow medical practitioners to use this information to optimize the treatment of a patient. Personalized oncology for groups of individuals would also allow for the use of population group specific diagnostic or prognostic biomarkers. Additionally, this information can be used to track the progress of the disease or monitor the response of the patient to treatment. This can be used to establish the molecular basis for drug resistance and allow the targeting of the genes or pathways responsible for drug resistance. Personalized medicine requires the use of large data sets, which must be processed and analysed in order to identify the particular molecular patterns that can inform the decisions required for personalized care. However, the analysis of these large data sets is difficult and time consuming. This is further compounded by the increasing size of these datasets due to technologies such as next generation sequencing (NGS). These difficulties can be met through the use of artificial intelligence (AI) and machine learning (ML). These computational tools use specific neural networks, learning methods, decision making tools and algorithms to construct and improve on models for the analysis of different types of large data sets. These tools can also be used to answer specific questions. Artificial intelligence can also be used to predict the effects of genetic changes on protein structure and therefore function. This review will discuss the current state of the application of AI to omics data, specifically genomic data, and how this is applied to the development of personalized or precision medicine on the treatment of cancer.
Clinical decision support: progress and opportunities Lyman, Jason A; Cohn, Wendy F; Bloomrosen, Meryl ...
Journal of the American Medical Informatics Association : JAMIA,
09/2010, Letnik:
17, Številka:
5
Journal Article
BACKGROUND: Recent technological advances in integrated circuits, wireless communications, and physiological sensing allow miniature, lightweight, ultra-low power, intelligent monitoring devices. A ...number of these devices can be integrated into a Wireless Body Area Network (WBAN), a new enabling technology for health monitoring. METHODS: Using off-the-shelf wireless sensors we designed a prototype WBAN which features a standard ZigBee compliant radio and a common set of physiological, kinetic, and environmental sensors. RESULTS: We introduce a multi-tier telemedicine system and describe how we optimized our prototype WBAN implementation for computer-assisted physical rehabilitation applications and ambulatory monitoring. The system performs real-time analysis of sensors' data, provides guidance and feedback to the user, and can generate warnings based on the user's state, level of activity, and environmental conditions. In addition, all recorded information can be transferred to medical servers via the Internet and seamlessly integrated into the user's electronic medical record and research databases. CONCLUSION: WBANs promise inexpensive, unobtrusive, and unsupervised ambulatory monitoring during normal daily activities for prolonged periods of time. To make this technology ubiquitous and affordable, a number of challenging issues should be resolved, such as system design, configuration and customization, seamless integration, standardization, further utilization of common off-the-shelf components, security and privacy, and social issues.
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