Among CEOs in the CEE region, 43 percent predicted that the global economy would slow down in 2020. A third predicted that it would remain the same, and about a quarter - that it would speed up.

Saudi Arabia: Economic growth forecast: The latest value from 2030 is 3.28 percent, an increase from 3.18 percent in 2029. In comparison, the world average is 3.25 percent, based on data from 182 countries. Historically, the average for Saudi Arabia from 1980 to 2030 is 2.25 percent. The minimum value, -16.11 percent, was reached in 1982 while the maximum of 10.99 percent was recorded in 2011.

In a March 2021 study of the out-of-home advertising market in the United Kingdom it was predicted that along with lifting of restrictions the OOH ad exposure will be gradually rising in the country. The first location to see the biggest change compared to a regular OOH advertising period would be roadside, at 25 percent growth in exposure, followed by small and large formats with 11 and six percent increase, respectively. Given that the country fully reopens by June 2021, the OOH industry will see lift in audience exposure of up to 40 percent.

Fiji: Economic growth forecast: The latest value from 2030 is 3.21 percent, an increase from 3.17 percent in 2029. In comparison, the world average is 3.25 percent, based on data from 182 countries. Historically, the average for Fiji from 1980 to 2030 is 2.41 percent. The minimum value, -17.04 percent, was reached in 2020 while the maximum of 19.79 percent was recorded in 2022.

AI Pulmonary Nodule Growth Prediction Market Outlook

According to the latest research conducted in 2025, the global AI Pulmonary Nodule Growth Prediction market size is valued at USD 1.18 billion in 2024. The market is expected to grow at a robust CAGR of 24.3% from 2025 to 2033, reaching a forecasted value of USD 9.81 billion by 2033. The primary growth factor driving this remarkable expansion is the rising adoption of artificial intelligence in medical imaging, particularly for early detection and precise monitoring of pulmonary nodules, which are critical in the management and prognosis of lung cancer.

The AI Pulmonary Nodule Growth Prediction market is experiencing significant momentum due to the increasing prevalence of lung cancer globally, which remains one of the leading causes of cancer-related deaths. The demand for advanced diagnostic solutions is escalating as healthcare providers seek to improve early detection rates and patient outcomes. AI-based tools offer enhanced accuracy and efficiency in identifying and predicting the growth of pulmonary nodules, allowing for timely intervention and more personalized treatment plans. This technological advancement reduces the rate of false positives and negatives, which has historically been a major challenge in traditional radiology, thus driving the adoption of AI-powered solutions across the healthcare sector.

Another critical growth factor is the rapid integration of AI technologies with existing imaging modalities, such as CT and MRI scanners. The seamless interoperability of AI software with hospital information systems and Picture Archiving and Communication Systems (PACS) allows clinicians to access predictive analytics directly within their workflow. This integration not only streamlines diagnostic processes but also supports multidisciplinary decision-making, which is essential in complex cases involving pulmonary nodules. Furthermore, continuous advancements in deep learning algorithms and cloud computing have made these solutions more scalable and accessible, even for smaller healthcare facilities and research institutes, thereby expanding the total addressable market.

The market is also benefitting from supportive regulatory frameworks and growing investments in healthcare AI research. Regulatory agencies in major markets such as the United States, Europe, and Asia Pacific are increasingly recognizing the value of AI in medical diagnostics and are accelerating the approval processes for AI-based medical devices. Additionally, public and private sector investments in digital healthcare infrastructure are fueling the development and deployment of AI-powered pulmonary nodule prediction systems. These factors, combined with a growing awareness among clinicians about the benefits of AI-enhanced diagnostics, are propelling the market forward at an unprecedented pace.

From a regional perspective, North America currently dominates the AI Pulmonary Nodule Growth Prediction market, accounting for the largest share in 2024, followed closely by Europe and Asia Pacific. The high adoption rate of advanced medical technologies, robust healthcare infrastructure, and strong presence of leading AI solution providers are the primary drivers in these regions. Meanwhile, Asia Pacific is expected to exhibit the fastest CAGR over the forecast period, driven by rapid digitalization of healthcare, increasing government initiatives, and a growing patient pool. Latin America and the Middle East & Africa are also witnessing gradual uptake, supported by improvements in healthcare delivery and rising investments in AI-based diagnostic tools.

Component Analysis

The Component segment of the AI Pulmonary Nodule Growth Prediction market is categorized into Software, Hardware, and Services. Software holds the largest market share in 2024, owing to its pivotal role in enabling predictive analytics, deep learning, and image processing functionalities. AI-powered software platforms are continuously evolving, off

The growth of the real gross domestic product (GDP) in Gabon was estimated at approximately 3.07 percent in 2024. Between 1981 and 2024, the growth rose by around 7.07 percentage points, though the increase followed an uneven trajectory rather than a consistent upward trend. The growth is forecast to decline by about 0.20 percentage points from 2024 to 2030, fluctuating as it trends downward.This indicator describes the annual change in the gross domestic product at constant prices, expressed in national currency units. Here the gross domestic product represents the total value of the final goods and services produced during a year.

Population by San Diego Region from the Series 14 Regional Growth Forecast

Analysis of ‘Startup Success Prediction’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/manishkc06/startup-success-prediction on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

A startup or start-up is a company or project begun by an entrepreneur to seek, develop, and validate a scalable economic model. While entrepreneurship refers to all new businesses, including self-employment and businesses that never intend to become registered, startups refer to new businesses that intend to grow large beyond the solo founder. Startups face high uncertainty and have high rates of failure, but a minority of them do go on to be successful and influential. Some startups become unicorns: privately held startup companies valued at over US$1 billion. [Source of information: Wikipedia] https://images.unsplash.com/photo-1556761175-5973dc0f32e7?ixlib=rb-1.2.1&ixid=eyJhcHBfaWQiOjEyMDd9&auto=format&fit=crop&w=500&q=60" alt="startup image"> Startups play a major role in economic growth. They bring new ideas, spur innovation, create employment thereby moving the economy. There has been an exponential growth in startups over the past few years. Predicting the success of a startup allows investors to find companies that have the potential for rapid growth, thereby allowing them to be one step ahead of the competition.

Objective

The objective is to predict whether a startup which is currently operating turns into a success or a failure. The success of a company is defined as the event that gives the company's founders a large sum of money through the process of M&A (Merger and Acquisition) or an IPO (Initial Public Offering). A company would be considered as failed if it had to be shut down.

About the Data

The data contains industry trends, investment insights and individual company information. There are 48 columns/features. Some of the features are:

• age_first_funding_year – quantitative
• age_last_funding_year – quantitative
• relationships – quantitative
• funding_rounds – quantitative
• funding_total_usd – quantitative
• milestones – quantitative
• age_first_milestone_year – quantitative
• age_last_milestone_year – quantitative
• state – categorical
• industry_type – categorical
• has_VC – categorical
• has_angel – categorical
• has_roundA – categorical
• has_roundB – categorical
• has_roundC – categorical
• has_roundD – categorical
• avg_participants – quantitative
• is_top500 – categorical
• status(acquired/closed) – categorical (the target variable, if a startup is ‘acquired’ by some other organization, means the startup succeed)

Acknowledgements

• I would like to thank Ramkishan Panthena, for providing us this dataset. He is a Machine Learning Engineer at GMO.
• This dataset was used in data sprint #5 at DPhi.

Inspiration

Predicting the success of a startup allows investors to find companies that have the potential for rapid growth, thereby allowing them to be one step ahead of the competition.

--- Original source retains full ownership of the source dataset ---

The Industrial Ethernet Market Report is Segmented by Offering (Hardware, Software, and Services), Protocol (EtherNet/IP, PROFINET, Ethercat, and More), Type (Managed Switches and Unmanaged Switches), Industry Vertical (Automotive, Aerospace and Defense, Electrical and Electronics, Energy and Utilities, and More), and Geography.

The Data Analytics Market size was valued at USD 41.05 USD billion in 2023 and is projected to reach USD 222.39 USD billion by 2032, exhibiting a CAGR of 27.3 % during the forecast period. Data Analytics can be defined as the rigorous process of using tools and techniques within a computational framework to analyze various forms of data for the purpose of decision-making by the concerned organization. This is used in almost all fields such as health, money matters, product promotion, and transportation in order to manage businesses, foresee upcoming events, and improve customers’ satisfaction. Some of the principal forms of data analytics include descriptive, diagnostic, prognostic, as well as prescriptive analytics. Data gathering, data manipulation, analysis, and data representation are the major subtopics under this area. There are a lot of advantages of data analytics, and some of the most prominent include better decision making, productivity, and saving costs, as well as the identification of relationships and trends that people could be unaware of. The recent trends identified in the market include the use of AI and ML technologies and their applications, the use of big data, increased focus on real-time data processing, and concerns for data privacy. These developments are shaping and propelling the advancement and proliferation of data analysis functions and uses. Key drivers for this market are: Rising Demand for Edge Computing Likely to Boost Market Growth. Potential restraints include: Data Security Concerns to Impede the Market Progress . Notable trends are: Metadata-Driven Data Fabric Solutions to Expand Market Growth.

Nicaragua: Economic growth forecast: The latest value from 2030 is 3.5 percent, unchanged from 3.5 percent in 2029. In comparison, the world average is 3.25 percent, based on data from 182 countries. Historically, the average for Nicaragua from 1980 to 2030 is 2.5 percent. The minimum value, -12.4 percent, was reached in 1988 while the maximum of 10.45 percent was recorded in 2021.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Daktronics (DAKT) Poised for Growth in the Digital Signage Revolution

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Forecast: Computer Hardware Productivity Growth Rate in the US 2022 - 2026 Discover more data with ReportLinker!

The U.S. electrical equipment market was valued at USD 520.4 billion in 2024 and is projected to reach USD 771.7 billion by 2032, growing at a 5.2% CAGR.

The Gross Domestic Product (GDP) in Colombia expanded 0.80 percent in the first quarter of 2025 over the previous quarter. This dataset provides - Colombia GDP Growth Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Vietnam’s real gross domestic product (GDP) has been experiencing positive growth for the past five years since 2019, and is projected to continue to do so through 2030. In 2023, Vietnam’s real GDP increased by around five percent compared to the previous year. Learning from real GDP Real gross domestic product (GDP) is a measure that reflects the value of all goods and services an economy produces within a given year. It is expressed in base-year prices, and is thus an inflation-adjusted way to compare a country’s economic output through the years. The GDP growth rate is a significant indicator of a country’s economic health, as it reacts to the economy’s expansions and contractions. Vietnam’s optimistic future As indicated by the positive growth rate of its real GDP, Vietnam’s economy is expanding due to growth in exports, domestic demand, and the manufacturing sector. As the economy expands, so does the total expenditure of Vietnamese consumers. The average monthly income per capita in Vietnam increased to almost 3.8 percent in 2018, and is spent on fast moving consumer goods from popular brands like Vinamilk and P/S.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Ohmyhome's (OMH) Outlook: Optimistic Growth Predicted Amidst Expansion Plans

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Slovakia SK: GDP: Growth: Volume: Exports of Goods and Services data was reported at 2.998 % in Dec 2026. This records a decrease from the previous number of 3.009 % for Sep 2026. Slovakia SK: GDP: Growth: Volume: Exports of Goods and Services data is updated quarterly, averaging 5.050 % from Jun 1992 (Median) to Dec 2026, with 139 observations. The data reached an all-time high of 215.320 % in Sep 2020 and a record low of -63.946 % in Jun 2020. Slovakia SK: GDP: Growth: Volume: Exports of Goods and Services data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Slovakia – Table SK.OECD.EO: GDP: Growth and Contribution to Growth: Forecast: OECD Member: Quarterly. XGSV_ANNPCT - Exports of goods and services, volume, growth (national accounts basis). Percentage change compared to the previous period. Quarterly growth expressed at annual rate.

Slovakia SK: GDP: Growth: Volume: Imports of Goods and Services: Double Hit Scenario data was reported at 12.000 % in Dec 2021. This stayed constant from the previous number of 12.000 % for Sep 2021. Slovakia SK: GDP: Growth: Volume: Imports of Goods and Services: Double Hit Scenario data is updated quarterly, averaging 5.798 % from Jun 1992 (Median) to Dec 2021, with 119 observations. The data reached an all-time high of 115.978 % in Mar 1996 and a record low of -65.000 % in Jun 2020. Slovakia SK: GDP: Growth: Volume: Imports of Goods and Services: Double Hit Scenario data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Slovakia – Table SK.OECD.EO: GDP: Growth and Contribution to Growth: Forecast: OECD Member: Quarterly. MGSV_ANNPCT - Imports of goods and services, volume, growth (national accounts basis). Percentage change compared to the previous period. Quarterly growth expressed at annual rate.

Components of projected population growth by scenario: births, deaths, immigrants, emigrants, returning emigrants, net temporary emigrants, net interprovincial migration, net non-permanent residents, residual deviation.