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Artificial Intelligence in Ultrasound Imaging Market Valuation to Hit USD 1825 Million by 2031

Artificial Intelligence in Ultrasound Imaging Market turns out to be the hotbed for the incumbents and the new entrants. The fact that healthcare industry is experiencing a drastic change moving from traditional ways to more advanced and analytical forms. The driving factors are highly supported by the adoption of the latest technologies in the developed nations and the urge by the emerging economies to get along with it will be impacting the overall demand positively. The government support and the initiatives taken by private organisations to improve the overall landscape will make the market reach its highest potential despite external adversities.

Market Size:

The estimated value of Artificial Intelligence in Ultrasound Imaging Market by 2031 will be USD 1825 Mn as the base year was valued at USD 934.99 Mn in 2023.

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List of Key Companies Profiled in Artificial Intelligence in Ultrasound Imaging Market Report:

  • IBM
  • Nvidia Corporation
  • Intel Corporation
  • Microsoft
  • Medtronic
  • Samsung
  • Butterfly network
  • GE Company
  • Siemens Healthcare
  • Johnson & Johnson
  • General Vision

“White Space in the Changing Landscape of Ultrasound Imaging”

The rising number of startups in the developed nations where the business model is AI concentrated is worth noticing element which guarantees the opportunities the market has to offer. SNS Insider quantified the YoY growth of AI startups in healthcare. The growth observed was 39%, and the growth will be equivalent throughout the forecasted period. The fact which is encouraging the startups is the white space which the market currently holds. The white space is mostly coming from the support by the government initiatives of developed nations, to improve the current landscape of the healthcare industry. This objective will be to improve the overall growth and market demand for Artificial Intelligence in the Ultrasound Imaging Market.

The factors which will obstruct the growth of the market are the high cost, lack of core competencies and the need of high-tech infrastructure. The developing nations are thus improving the overall funding but our analysis predicts the external impacts of slow macro-economic conditions will hamper the market growth in developing economies.

Artificial Intelligence in Ultrasound Imaging Market
Artificial Intelligence in Ultrasound Imaging Market

Key Market Segmentation:

By Technology

  • Machine Learning
  • Computer vision
  • Natural Language Processing
  • Others

By Application

  • Radiology
  • Obstetrics
  • Gynecology
  • Cardiovascular
  • Others

By End User

  • Hospitals
  • Patients
  • Healthcare Payers
  • Others

Segment Analysis:

The Artificial Intelligence in Ultrasound Imaging Market segment analysis includes the study of three major segments i.e., by technology, by application and by end User. In the technology segment machine learning will be holding the maximum share. The most important segment will be applications. Because the market growth is dependent on how the implementation of the latest technology is been done for the various chronic diseases. The in-depth analysis includes the share of how every sub-segment will be performing in the future and what factors will make the sub-segments attract maximum revenue.

Radiology will be the sub-segment in the by-applications segment which will hold the highest share. The estimated share will be 38% over the forecast period.

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Regional Analysis:

The rising number of startups in the U.S. and the increase in the overall prevalence of cancer and cardiovascular diseases will be making the market attend more revenue generation from the developed nations of North America. Undoubtedly U.S. will be the nation which will be holding the share of 80% along with CANADA which will have the highest CAGR growth rate.

Focusing on the emerging economies which are considered as the marketplace to improve the player’s market growth opportunities. There are several positive factors and negative factors which will dictate the overall scenarios. Some of the key insights include the high adoption rates of the latest technologies. The rising investments in the implementation of infrastructure will be equivalent to the need for the latest technology.

Key Takeaways:

  • The rising prevalence of people suffering from cancer will ultimately improve the demand for Artificial Intelligence in Ultrasound Imaging. For instance, according to the American Cancer Society, the U.S. will be experiencing more than 2 Mn new cases in 2024.
  • The opportunities lie within the market, as the high awareness and the high adoption rates in the developed economies will improve the overall valuation of the Artificial Intelligence in Ultrasound Imaging Market.
  • CEOs will be experiencing moderate turbulence of macro-economic turmoil, as the demand factor will be overlapping the adversities.

Competitive Landscape:

  • Many tech giants are implementing the diversification strategy, as the high market valuation is encouraging them to do so. The developments of hardware and software by Nvidia which is based on the requirements of the healthcare industry. The platform name is called Nvidia Clara platform.
  • Similarly, IBM has also started gaining traction and putting out several innovations which are AI-centric and have high-value propositions aligned with the recent and future trends of healthcare industry.

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Table of Content

Chapter 1 Introduction

Chapter 2 Research Methodology

Chapter 3 Artificial Intelligence in Ultrasound Imaging Market Dynamics

Chapter 4 Impact Analysis (COVID-19, Ukraine- Russia war, Ongoing Recession on Major Economies)

Chapter 5 Value Chain Analysis

Chapter 6 Porter’s 5 forces model

Chapter 7 PEST Analysis

Chapter 8 Artificial Intelligence in Ultrasound Imaging Market Segmentation, By Technology

Chapter 9 Artificial Intelligence in Ultrasound Imaging Market Segmentation, By Application

Chapter 10 Artificial Intelligence in Ultrasound Imaging Market Segmentation, By End User

Chapter 11 Regional Analysis

Chapter 12 Company profile

Chapter 13 Competitive Landscape

Chapter 14 Use Case and Best Practices

Chapter 15 Conclusion


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