scholarly journals Use of Machine Learning for Long Term Planning and Cost Minimization in Healthcare Management

2021 ◽  
Author(s):  
Sadia Binta Kabir ◽  
Salman Sadiq Shuvo ◽  
Helal Uddin Ahmed
Keyword(s):  
Reinforcement Learning ◽  
Capacity Planning ◽  
Cost Minimization ◽  
Capacity Expansion ◽  
Developed Countries ◽  
Healthcare Management ◽  
Best Interest ◽  
Healthcare Facilities ◽  
Expansion Plan

AbstractThe Healthcare system of a country is a crucial infrastructure that requires long-term capacity planning. The covid 19 outbreak pointed to the necessity of adequate hospital capacity, especially for developing countries like Bangladesh. The existing infrastructure planning of these countries emphasizes short-term goals and lacks vision planning for a long time horizon. It is in the country’s best interest to make long-term capacity expansion plans, a strategy the developed countries banked to provide adequate healthcare facilities to their residents. However, no single solution is appropriate for a different region. Hence, it is required to comprehensively study the situation and constraints of the specific region before providing expensive capacity expansion plans. This work focuses on applying a deep Reinforcement Learning based long-term hospital bed capacity expansion plan. We utilize the RNN-LSTM based population forecast, deep Reinforcement Learning (RL) based policy-making, and state-of-the-art Artificial Intelligence techniques to provide a solution. We perform a case study for the Abhaynagar Upazila of Jessore, one of the largest cities in the southwest part of Bangladesh, to analyze the benefits of such an approach compared to existing myopic policies. The experiment results show that the deep RL-based policy significantly minimizes cost over a 30-year expansion plan.

Conditions for the Hi-tech Complex Development

2003 ◽  
pp. 26-39
Author(s):  
V. Maevsky ◽  
B. Kuzyk
Keyword(s):  
Economic Development ◽  
Central Bank ◽  
Developed Countries ◽  
Industrial Society ◽  
Monetary Base ◽  
Complex Development ◽  
Bank System ◽  
Post Industrial

A project for the long-term strategy of Russian break-through into post-industrial society is suggested which is directed at transformation of the hi-tech complex into the leading factor of economic development. The thesis is substantiated that there is an opportunity to realize such a strategy in case Russia shifts towards the mechanism of the monetary base growth generally accepted in developed countries: the Central Bank increases the quantity of "strong" money by means of purchasing state securities and allocates the increment of money in question according to budget priorities. At the same time for the realization of the said strategy it is necessary to partially restore savings lost during the hyperinflation period of 1992-1994 and default of 1998 and to secure development of the bank system as well as an increase of the volume of long-term credits on this base.

The Reproduction Vector of the Russian Economy: 1999-2007

2008 ◽  
pp. 94-109 ◽  
Author(s):  
D. Sorokin
Keyword(s):  
Economic Policy ◽  
Human Capital ◽  
Growth Rates ◽  
Developed Countries ◽  
Gdp Per Capita ◽  
Real Sector ◽  
Russian Economy ◽  
Per Capita ◽  
The Developed Countries

The problem of the Russian economy’s growth rates is considered in the article in the context of Russia’s backwardness regarding GDP per capita in comparison with the developed countries. The author stresses the urgency of modernization of the real sector of the economy and the recovery of the country’s human capital. For reaching these goals short- or mid-term programs are not sufficient. Economic policy needs a long-term (15-20 years) strategy, otherwise Russia will be condemned to economic inertia and multiplying structural disproportions.

PENGARUH INFRASTRUKTUR SECARA SPASIAL TERHADAP KONVERGENSI PERTUMBUHAN EKONOMI DI INDONESIA

INFO ARTHA ◽  
2017 ◽  
Vol 1 ◽  
pp. 17-28
Author(s):  
Anisa Fahmi
Keyword(s):  
Economic Growth ◽  
Regional Economics ◽  
Developed Countries ◽  
Road Infrastructure ◽  
Long Run ◽  
Catch Up ◽  
The Developed Countries ◽  
Positive Effect ◽  
Neoclassical Growth Theory

Motivated by inter-regional disparities condition that occurs persistently, this study examines the Indonesian economy in the long run in order to know whether it tends to converge or diverge. This convergence is based on the Solow Neoclassical growth theory assuming the existence of diminishing returns to capital so that when the developed countries reach steady state conditions, developing countries will continuously grow up to 'catch-up' with developed countries. Based on regional economics perspective, each region can not be treated as a stand-alone unit,therefore, this study also focuses on the influence of spatial dependency and infrastructure. Economical and political situations of a region will influence policy in that region which will also have an impact to the neighboring regions. The estimation results of spatial cross-regressive model using fixed effect method consistently confirmed that the Indonesian economy in the long term will likely converge with a speed of 8.08 percent per year. Other findings are road infrastructure has a positive effect on economic growth and investment and road infrastructure are spatially showed a positive effect on economic growth. In other words, the investment and infrastructure of a region does not only affect the economic growth of that region but also to the economy of the contiguous regions. 

The Influence of Growth, Asset Tangibility, Cost of Debt, Profitability and Business Risk On Debt Capital

2019 ◽  
Vol 4 (4) ◽  
pp. 120-127
Author(s):  
Erika Jimena Arilyn ◽  
Beny Beny
Keyword(s):  
Firm Growth ◽  
Stock Exchange ◽  
Panel Data Analysis ◽  
Developed Countries ◽  
Jel Classification ◽  
Cost Of Debt ◽  
Market Condition ◽  
Business Risk ◽  
Debt Capital

Objective –The aims to identify the significant factors that influence a company’s decision to use debt capital. Methodology/Technique – This study uses 5 independent variables namely; firm growth (growth rate in total gross assets), asset tangibility (ratio of net fixed assets to total assets), cost of debt (interest before tax / long term debt), profitability (Earnings Before Interest and Taxes (EBIT) / Total Asset), and business risk (standard deviation of EBIT to total assets). The dependent variable in this study, debt capital, is measured by the ratio of long-term debt to total assets. A purposive sampling method is used to select 11 out of 18 textile and garment companies listed on the Indonesian Stock Exchange between 2014 and 2018 that report their annual financial positions. A quantitative method, panel data analysis technique and SPSS tools were also used in this study. Findings – The results show that debt capital is influenced by profitability, while the remaining factors do not influence debt capital. Novelty – This study adds to the existing literature on internal factors, market condition as an external factors, and debt capital in developed countries. The benefit of this study is to explore the potential capabilities of the industry in using its profit to minimize the use of debt as a source of capital to decrease business risk. Type of Paper: Empirical Keywords: Profitability; Growth; Cost of Debt; Business Risk; Tangibility; Capital Structure. Reference to this paper should be made as follows: Ariyln, E., J; Beny; 2019. The Influence of Growth, Asset Tangibility, Cost Of Debt, Profitability and Business Risk On Debt Capital, Acc. Fin. Review 4 (4): 120 – 127 https://doi.org/10.35609/afr.2019.4.4(4) JEL Classification: G23, G32.

Long Term Prognostic Utility of Matrix Metalloproteinase-9 in Patients with Acute Coronary Syndrome – A Systematic Review

2020 ◽  
Vol 21 ◽  
Author(s):  
Anamika Das ◽  
Melvin George ◽  
Durga Jha ◽  
Luxitaa Goenka
Keyword(s):  
Acute Coronary Syndrome ◽  
High Risk ◽  
Matrix Metalloproteinase ◽  
Developed Countries ◽  
Left Ventricular ◽  
Original Research ◽  
Coronary Syndrome ◽  
Potential Biomarker ◽  
Prognostic Utility

Background: Acute coronary syndrome (ACS) is the leading cause for morbidity and mortality in developed countries. Numerous groups have explored single and multiple biomarker strategies to identify diagnostic prognosticators of ACS which will improve our ability to identify high-risk individuals. Matrix metalloproteinase (MMP-9) is one potential biomarker which has been widely studied in ACS. Recent reports have showed the prognostic utility of MMP-9, but due to inconsistent results, it has not been possible to draw firm conclusions. Objective: This review aims to explore the ability of MMP-9 to predict long-term prognosis of ACS. To clarify this issue, we conducted a literature review to provide a comprehensive assessment of MMP-9 levels in ACS patients. Method: We retrieved a total of 1501 articles from PubMed and Google Scholar. After thorough scrutiny, 12 original research articles were found fulfilling the inclusion exclusion criteria. MMP-9’s ability as a biomarker of prognostication post ACS was reviewed. PRISMA guidelines were used for reporting. Result: The results revealed that MMP-9, apart from being an efficient diagnostic biomarker for ACS, helps in predicting the future risk of ACS with disease outcome. Positive correlation was found between plasma MMP-9 and left ventricular remodeling. A positive association was also found between cardiovascular death and higher MMP-9 levels. Conclusion: MMP-9 can be a potential prognostic marker for ACS and aid in identifying high risk patients for intensive management during follow -up.

scholarly journals Anti-meningococcal B vaccination in Italian adolescents: a cost-effective health opportunity

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
D Panatto ◽  
P Landa ◽  
D Amicizia ◽  
P L Lai ◽  
E Lecini ◽  
...  
Keyword(s):  
Large Scale ◽  
Public Health Problem ◽  
Vaccination Strategy ◽  
Cost Effective ◽  
Dose Schedule ◽  
Developed Countries ◽  
Invasive Disease ◽  
International Setting ◽  
The Impact

Abstract Background Invasive disease due to Neisseria meningitidis (Nm) is a serious public health problem even in developed countries, owing to its high lethality rate (8-15%) and the invalidating sequelae suffered by many (up to 60%) survivors. As the microorganism is transmitted via the airborne route, the only available weapon in the fight against Nm invasive disease is vaccination. Our aim was to carry out an HTA to evaluate the costs and benefits of anti-meningococcal B (MenB) vaccination with Trumenba® in adolescents in Italy, while also considering the impact of this new vaccination strategy on organizational and ethics aspects. Methods A lifetime Markov model was developed. MenB vaccination with the two-dose schedule of Trumenba® in adolescents was compared with 'non-vaccination'. Two perspectives were considered: the National Health Service (NHS) and society. Three disease phases were defined: acute, post-acute and long-term. Epidemiological, economic and health utilities data were taken from Italian and international literature. The analysis was conducted by means of Microsoft Excel 2010®. Results Our study indicated that vaccinating adolescents (11th year of life) with Trumenba® was cost-effective with an ICER = € 7,912/QALY from the NHS perspective and € 7,758/QALY from the perspective of society. Vaccinating adolescents reduces the number of cases of disease due to meningococcus B in one of the periods of highest incidence of the disease, resulting in significant economic and health savings. Conclusions This is the first study to evaluate the overall impact of free MenB vaccination in adolescents both in Italy and in the international setting. Although cases of invasive disease due to meningococcus B are few, if the overall impact of the disease is adequately considered, it becomes clear that including anti-meningococcal B vaccination into the immunization program for adolescents is strongly recommended from the health and economic standpoints. Key messages Free, large-scale MenB vaccination is key to strengthening the global fight against invasive meningococcal disease. Anti-meningococcal B vaccination in adolescents is a cost-effective health opportunity.

scholarly journals MEG signatures of long-term effects of agreement and disagreement with the majority

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
A. Gorin ◽  
V. Klucharev ◽  
A. Ossadtchi ◽  
I. Zubarev ◽  
V. Moiseeva ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Social Influence ◽  
Temporal Dynamics ◽  
Peer Group ◽  
Long Term Effects ◽  
Learning Mechanisms ◽  
Source Imaging ◽  
The Face ◽  
First Session

AbstractPeople often change their beliefs by succumbing to an opinion of others. Such changes are often referred to as effects of social influence. While some previous studies have focused on the reinforcement learning mechanisms of social influence or on its internalization, others have reported evidence of changes in sensory processing evoked by social influence of peer groups. In this study, we used magnetoencephalographic (MEG) source imaging to further investigate the long-term effects of agreement and disagreement with the peer group. The study was composed of two sessions. During the first session, participants rated the trustworthiness of faces and subsequently learned group rating of each face. In the first session, a neural marker of an immediate mismatch between individual and group opinions was found in the posterior cingulate cortex, an area involved in conflict-monitoring and reinforcement learning. To identify the neural correlates of the long-lasting effect of the group opinion, we analysed MEG activity while participants rated faces during the second session. We found MEG traces of past disagreement or agreement with the peers at the parietal cortices 230 ms after the face onset. The neural activity of the superior parietal lobule, intraparietal sulcus, and precuneus was significantly stronger when the participant’s rating had previously differed from the ratings of the peers. The early MEG correlates of disagreement with the majority were followed by activity in the orbitofrontal cortex 320 ms after the face onset. Altogether, the results reveal the temporal dynamics of the neural mechanism of long-term effects of disagreement with the peer group: early signatures of modified face processing were followed by later markers of long-term social influence on the valuation process at the ventromedial prefrontal cortex.

Business-Driven Long-Term Capacity Planning for SaaS Applications

2015 ◽  
Vol 3 (3) ◽  
pp. 290-303 ◽  
Author(s):  
David Candeia ◽  
Ricardo Araujo Santos ◽  
Raquel Lopes
Keyword(s):  
Capacity Planning
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