Evolution of a multi-stakeholder initiative of health promotion in 20 suburban Roman districts

Corsaro, A; Sisti, Leuconoe Grazia; Parente, Paolo; Galizi, MC; Giuffrida, Giovanni; Pietro, ML Di; Damiani, Gianfranco

doi:10.1093/eurpub/cky218.296

Cited by 2 publications

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“…e recognition method based on neural network takes the index embedding vector as input, trains the correctly recognized data to automatically learn features and train models, and then identifies the test data with the trained model. e recognition method based on neural network avoids the traditional feature engineering and has a good effect on the problem of unregistered recognition [23,24]. Compared with other traditional recognition methods, the overall recognition effect of bidirectional long-short term memory model has obvious advantages.…”

Section: Background and Related Workmentioning

confidence: 99%

Identification and Early Warning of Financial Fraud Risk Based on Bidirectional Long-Short Term Memory Model

Liu

Fan

2022

Mathematical Problems in Engineering

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In modern market economy, corporate financial frauds emerge one after another, which have a huge impact on the stock market and triggered an unprecedented credit crisis. Therefore, it is particularly important to identify financial frauds. Improving the efficiency, accuracy, and coverage of fraud identification in financial reports through digital and intelligent means is one of the important links to improve credit risk control of securities companies and also for securities companies to accurately price related financial products of target companies. Traditional recognition methods based on artificial rules can cover relatively limited indicators; rule parameters are set randomly. Besides, it is difficult to make rules based on high-dimension indicators and to dig the hidden deep relationships between indicators. This paper summarizes the relevant indicators of financial fraud identification from the perspective of financial and nonfinancial characteristics. Then, the identification and early warning of financial fraud risk based on bidirectional long-short term memory model are proposed. This method uses the idea of ensemble learning, weights the probability of financial key indicators, and uses the optimal transfer probability to solve the financial fraud risk results. The results show that the industry-specific modeling can significantly improve the accuracy of the financial fraud identification model and it also can effectively help the government regulatory departments, investors, and audit departments to correctly identify the financial fraud of listed companies.

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Section: Background and Related Workmentioning

confidence: 99%

Identification and Early Warning of Financial Fraud Risk Based on Bidirectional Long-Short Term Memory Model

Liu

Fan

2022

Mathematical Problems in Engineering

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“…erefore, the existing price supervision model provides the feasibility for public hospitals to maintain their overall profit level through the above "cross-subsidy" method. From the perspective of public hospitals' interests, government price regulation has achieved a "win-win" between the medical service market and public hospitals [21][22][23].…”

Section: From the Perspective Of Public Hospitals' Interestsmentioning

confidence: 99%

Medical Diagnosis Decision Based on Psychological Cognition Difference of Multistakeholder

Wei

2022

Mathematical Problems in Engineering

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This paper firstly reviews the achievements and existing problems of China’s government in the supervision of medical service price in public hospitals in recent years. On this basis, patient’s interests, the interests of the public hospital, medical staff perspective, analysis of the three main psychological cognitive differences’ influence on medical diagnosis strategy, and the utility of public hospital medical service price regulation are analyzed, and accordingly perfect China’s public hospital medical service price regulation suggestions are put forward. In this paper, taking a medical institution as an example, combined with the psychological cognitive differences of multi-interest theme, and through research, it is shown that the causes of influencing the unreasonable admission behavior of patients in medical institutions are as follows: first, the characteristics of vulnerable groups of patients affect the unreasonable admission behavior, mainly children and the elderly. Second, the health risk avoidance psychology drives patients to be hospitalized unreasonably, especially those with chronic diseases or those who pay attention to their own health. Third, the influence of convenience degree on unreasonable admission is relatively small. Fourth, doctor’s advice has an important influence on unreasonable admission behavior. Fifth, the medical insurance system affects the unreasonable admission behavior of patients to a certain extent.

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Evolution of a multi-stakeholder initiative of health promotion in 20 suburban Roman districts

Cited by 2 publications

References 0 publications

Identification and Early Warning of Financial Fraud Risk Based on Bidirectional Long-Short Term Memory Model

Identification and Early Warning of Financial Fraud Risk Based on Bidirectional Long-Short Term Memory Model

Medical Diagnosis Decision Based on Psychological Cognition Difference of Multistakeholder

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