با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
ردیف | عنوان | نوع |
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1 |
Quantum Kernels for Real-World Predictions Based on Electronic Health Records
هستههای کوانتومی برای پیشبینیهای دنیای واقعی بر اساس پروندههای سلامت الکترونیکی-2022 Research on near-term quantum machine learning has explored how classical machine learning
algorithms endowed with access to quantum kernels (similarity measures) can outperform their purely
classical counterparts. Although theoretical work has shown a provable advantage on synthetic data sets,
no work done to date has studied empirically whether the quantum advantage is attainable and with what
data. In this article, we report the first systematic investigation of empirical quantum advantage (EQA) in
healthcare and life sciences and propose an end-to-end framework to study EQA. We selected electronic
health records data subsets and created a configuration space of 5–20 features and 200–300 training samples.
For each configuration coordinate, we trained classical support vector machine models based on radial basis
function kernels and quantum models with custom kernels using an IBM quantum computer, making this
one of the largest quantum machine learning experiments to date. We empirically identified regimes where
quantum kernels could provide an advantage and introduced a terrain ruggedness index, a metric to help
quantitatively estimate how the accuracy of a given model will perform. The generalizable framework introduced here represents a key step toward a priori identification of data sets where quantum advantage could
exist.
INDEX TERMS: Artificial intelligence | digital health | electronic health records (EHR) | empirical quantum advantage (EQA) | machine learning | quantum kernels | real-world data | small data sets | support vector machines (SVM). |
مقاله انگلیسی |
2 |
When digital health meets digital capitalism, how many common goods are at stake?
هنگامی که سلامت دیجیتال با سرمایه داری دیجیتال ملاقات می کند، چندین کالای مشترک در معرض خطر هستند؟-2018 In recent years, all major consumer technology corporations have moved into the domain of health research. This
‘Googlization of health research’ (‘GHR’) begs the question of how the common good will be served in this research. As
critical data scholars contend, such phenomena must be situated within the political economy of digital capitalism in
order to foreground the question of public interest and the common good. Here, trends like GHR are framed within a
double, incommensurable logic, where private gain and economic value are pitted against public good and societal value.
While helpful for highlighting the exploitative potential of digital capitalism, this framing is limiting, insofar as it acknowledges only one conception of the common good. This article uses the analytical framework of modes of justification
developed by Boltanksi and The´venot to identify a plurality of orders of worth and conceptualizations of the common
good at work in GHR. Not just the ‘civic’ (doing good for society) and ‘market’ (enhancing wealth creation) orders, but
also an ‘industrial’ (increasing efficiency), a ‘project’ (innovation and experimentation), and what I call a ‘vitalist’ (proliferating life) order. Using promotional material of GHR initiatives and preliminary interviews with participants in GHR
projects, I ask what moral orientations guide different actors in GHR. Engaging seriously with these different conceptions
of the common good is paramount. First, in order to critically evaluate them and explicate what is at stake in the move
towards GHR, and ultimately, in order to develop viable governance solutions that ensure strong ‘civic’ components.
Keywords: Digital health | digital capitalism | Googlization of health research | moral repertoires | common good | public values |
مقاله انگلیسی |