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Models, Economic

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Effects of cost-benefit analysis under back propagation neural network on financial benefit evaluation of investment projects.

PloS one
To determine the influence of the weight of the economic effectiveness evaluation criteria of the major investments of listed enterprises, and provide new management ideas for the development of the follow-up enterprises, firstly, the financial benef...

Cost-aware active learning for named entity recognition in clinical text.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Active Learning (AL) attempts to reduce annotation cost (ie, time) by selecting the most informative examples for annotation. Most approaches tacitly (and unrealistically) assume that the cost for annotating each sample is identical. This ...

Fuzzy Model for Quantitative Assessment of Environmental Start-up Projects in Air Transport.

International journal of environmental research and public health
The purpose of this paper is to develop an applied fuzzy model of information technology to obtain quantitative estimates of environmental start-up projects in air transport. The developed model will become a useful tool for venture funds, business a...

Machine Learning for Health Services Researchers.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
BACKGROUND: Machine learning is increasingly used to predict healthcare outcomes, including cost, utilization, and quality.

Stock Market Forecasting Using Restricted Gene Expression Programming.

Computational intelligence and neuroscience
Stock index prediction is considered as a difficult task in the past decade. In order to predict stock index accurately, this paper proposes a novel prediction method based on S-system model. Restricted gene expression programming (RGEP) is proposed ...

Financial time series forecasting using twin support vector regression.

PloS one
Financial time series forecasting is a crucial measure for improving and making more robust financial decisions throughout the world. Noisy data and non-stationarity information are the two key factors in financial time series prediction. This paper ...

Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data.

PloS one
Forecasting stock prices plays an important role in setting a trading strategy or determining the appropriate timing for buying or selling a stock. We propose a model, called the feature fusion long short-term memory-convolutional neural network (LST...

Machine Learning and Primary Total Knee Arthroplasty: Patient Forecasting for a Patient-Specific Payment Model.

The Journal of arthroplasty
BACKGROUND: Value-based and patient-specific care represent 2 critical areas of focus that have yet to be fully reconciled by today's bundled care model. Using a predictive naïve Bayesian model, the objectives of this study were (1) to develop a mach...

Improving Stock Closing Price Prediction Using Recurrent Neural Network and Technical Indicators.

Neural computation
This study focuses on predicting stock closing prices by using recurrent neural networks (RNNs). A long short-term memory (LSTM) model, a type of RNN coupled with stock basic trading data and technical indicators, is introduced as a novel method to p...

Using machine learning to investigate self-medication purchasing in England via high street retailer loyalty card data.

PloS one
The availability alongside growing awareness of medicine has led to increased self-treatment of minor ailments. Self-medication is where one 'self' diagnoses and prescribes over the counter medicines for treatment. The self-care movement has importan...