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Hybrid deep learning models with multi-classification investor sentiment to forecast the prices of China's leading stocks.

PloS one
The prediction of stock prices has long been a captivating subject in academic research. This study aims to forecast the prices of prominent stocks in five key industries of the Chinese A-share market by leveraging the synergistic power of deep learn...

A performance comparison of machine learning models for stock market prediction with novel investment strategy.

PloS one
Stock market forecasting is one of the most challenging problems in today's financial markets. According to the efficient market hypothesis, it is almost impossible to predict the stock market with 100% accuracy. However, Machine Learning (ML) method...

Projected Growth in FDA-Approved Artificial Intelligence Products Given Venture Capital Funding.

Journal of the American College of Radiology : JACR
PURPOSE: Medical imaging accounts for 85% of digital health's venture capital funding. As funding grows, it is expected that artificial intelligence (AI) products will increase commensurately. The study's objective is to project the number of new AI ...

Improving the classification of veterinary thoracic radiographs through inter-species and inter-pathology self-supervised pre-training of deep learning models.

Scientific reports
The analysis of veterinary radiographic imaging data is an essential step in the diagnosis of many thoracic lesions. Given the limited time that physicians can devote to a single patient, it would be valuable to implement an automated system to help ...

Regional economic forecast using Elman neural networks with wavelet function.

PloS one
Recently, the economy in Guangdong province has ranked first in the country, maintaining a good growth momentum. The prediction of Gross Domestic Product (GDP) for Guangdong province is an important issue. Through predicting the GDP, it is possible t...

Evaluation and screening of technology start-ups based on PCA and GA-BPNN.

PloS one
PURPOSE: Due to the existence of information opacity, there is a common problem of adverse selection in the process of screening alternative technology start-ups (TSs) and determining investment targets by venture capital institutions, which does not...

A multinational study on artificial intelligence adoption: Clinical implementers' perspectives.

International journal of medical informatics
BACKGROUND: Despite substantial progress in AI research for healthcare, translating research achievements to AI systems in clinical settings is challenging and, in many cases, unsatisfactory. As a result, many AI investments have stalled at the proto...

Forecasting China carbon price using an error-corrected secondary decomposition hybrid model integrated fuzzy dispersion entropy and deep learning paradigm.

Environmental science and pollution research international
Forecasting China's carbon price accurately can encourage investors and manufacturing industries to take quantitative investments and emission reduction decisions effectively. The inspiration for this paper is developing an error-corrected carbon pri...

The role of artificial intelligence and fintech in promoting eco-friendly investments and non-greenwashing practices in the US market.

Journal of environmental management
This study explores the intricate connections among financial technology (FinTech), artificial intelligence (AI), and eco-friendly markets in the US, shedding light on their dynamic interplay and implications for sustainable investment and policy str...