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Clinical intelligence about a patient’s risk of future adverse health events can support clinical decision making in … address the challenging tasks of risk profiling. Patients with chronic diseases often face risks of not just one, but an array … of adverse health events. However, existing risk models typically focus on one specific event and do not predict multiple …
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Chapter 1. Introduction — Trends, Puzzles and Hopes for the Future of Healthcare -- Chapter 2. Innovations in Psychiatric Care Models: Lessons from the Past to Inform the Future -- Chapter 3. Mobile Sensors in Healthcare: Technical, Ethical, and Medical Aspects -- Chapter 4. New Horizons in...
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applied to visualise risk and to build robust portfolios of hedge fund managers. Essentially, it documents a feasibility study … right corners. Hedge Fund portfolios based on this method achieve more favourable risk/return ratios and lower drawdowns …
Persistent link: https://www.econbiz.de/10012907501
Model, to identify the risk factors discussed in 10-Ks. We apply this algorithm to a US REIT sample between 2005 and 2019 to … assess whether the probability of appearance of the extracted risk factors helps to explain the perceived risk on the stock … market. We find that the majority of risk factors is significantly associated with volatility indicating that our machine …
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The EU proposal for the Artificial Intelligence Act (AIA) defines four risk categories: unacceptable, high, limited …, and minimal. However, as these categories statically depend on broad fields of application of AI systems (AIs), the risk … to the risk scenarios of each AIs, rather than solely to its field of application. We address this model flaw by …
Persistent link: https://www.econbiz.de/10014359393
We demonstrate the value of machine learning in accounting through a detailed examination of litigation risk, an … prediction of litigation risk, with hourglass-shaped and convolutional neural networks the most effective. The improvements are … literature. We also produce firm-year litigation risk estimates for use in future research from a convolutional neural network …
Persistent link: https://www.econbiz.de/10014361830
-level climate risk exposure by utilising two natural language processing techniques (LDA and word2vec) on firms’ quarterly earnings … exposure, suggesting that firms’ disaster risk exposure significantly affects the cost of equity and market valuations. A long …-short portfolio based on this exposure measure generates a positive return of 5% per annum, which cannot be explained by common risk …
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