Technological advancements in the healthcare industry have delivered enormous benefits to society by fetching material improvements in quality of life and average life spans. Emerging technologies such as artificial intelligence (AI) are reshaping the healthcare landscape in immense ways.
Use of AI is rapidly evolving in the sector supporting functions from robotics surgeries to streamlining workflows in medical field to managing medical resources and patients.
AI has come a long way in assisting radiologists for accurate and better decision support systems. By improving the accuracy of predicting tumor malignancy and offering greater insights while diagnosis, AI is providing radiologists in several niche and sub domains of radiology.
It is supporting the computational powers of traditional radio-imaging techniques such as CAT-scans and MRI via complex algorithms such as deep learning and neural network. These higher computational capabilities, in turn, continue to enhance diagnostic imaging, thereby resulting in an improved and faster diagnosis.
Even though AI-enabled diagnostic imaging has paved its way and progressing at a faster pace, it is still relatively new in some of the verticals where AI has been implemented. In the current scenario, the adoption pace of AI in medical imaging is propelling the growth of the healthcare sector at an unprecedented rate.
For instance, in August 2020, University Medical Center (UMC) Utrecht and Philips kicked off a research partnership to improvise precision diagnosis through quantitative MRI technology with AI-enabled diagnostic imaging.
Impact of COVID-19 Pandemic Outbreak on AI-enabled Diagnostic Imaging Market
Medical centers and hospitals are getting overwhelmed by the sheer magnitude of the spread of novel coronavirus. Ongoing tech trends such as virtual healthcare management telemedicine and artificial intelligence are proving critical in tackling amidst this pandemic outbreak.
In such times there is a need for health systems that can reduce manual tasks which will further reduce the number of staff members. In addition big data analytics is helping to monitor the spread of the virus.
Medical images also helps in detection monitoring and diagnosis of diseases such as COVID-19 as it helps doctors to determine the severity of disease by reviewing CT scans or X-rays.
Thus the demand of artificial intelligence based diagnostic imaging solutions is increasing which if further fueling the growth of the market. Thus the AI-enabled diagnostic imaging market is anticipated to grow at a CAGR of 20-22% by the end of 2020 with an increase of almost 5% compared to that of previous year.
AI-enabled Diagnostic Imaging Market: Market Dynamics
AI-based Diagnostic Imaging in Healthcare Landscape Improves Care Models
The emergence of advanced AI tools and technology is poised to play a vital role in transforming the radiology and healthcare space in the near future. Greater adoption of AI in the medical vertical particularly in radiology is expected to offer a plethora of prospects for organizations in the current market for AI in medical imaging.
Major factor that will most likely enhance the adoption of AI in medical imaging is enlarging the gap between the augmenting numbers of available radiologists and numbers of scans that can read data.
Surging pressure to fasten the procedure of data interpretation along with workload resulted in a considerable increase in the number of errors. This in turn is presenting participants in the AI-enabled diagnostic imaging market a window of prospects to raise market presence.
Researchers and Enterprises Come Together to Create Proficient AI-based Platforms
Major players operating in the current AI-enabled diagnostic imaging market are poised to closely work with healthcare providers educational institutes and other stakeholders in order to develop cost-effective and technology advanced AI-enabled platforms for healthcare experts.
For instance in April 2019 the American College of Radiology (ACR) and Nvidia Corporation declared a collaboration to develop an open architecture AI system to aid radiologists to create advanced diagnostic algorithms.
Enterprises in the AI-enabled diagnostic imaging market are actively exploring the potential benefits by developing new deep learning models for improved image interpretation.
AI-enabled Diagnostic Imaging Market: Competition Landscape
Examples of some of the market participants in the global AI-enabled diagnostic imaging market identified across the value chain include
- Siemens Healthineers AG
- Nuance Communications Inc.
- Koninklijke Philips N.V.
- Arterys Inc.
- Samsung Electronics Co. Ltd.
- Zebra Medical Vision Inc.
- Resonance Health Ltd.
- Bay Labs Inc.
- IBM Corporation
Following are some key strategies and developments in the global AI-enabled diagnostic imaging market:
- In October 2019 Zebra Medical Vision partnered with Emergent Connect a cloud-based PACS software provider to improve healthcare experience and bring the power of artificial intelligence to Emergent Connect's growing customer base
AI-enabled Diagnostic Imaging Market: Regional Outlook
North America accords for the major shares in the AI-enabled diagnostic imaging market owing to the surging demand for artificial intelligence in the United State healthcare market coupled with the presence of a large number of strong players in the region.
On the contrary Europe is growing at an exponential rate in adoption of AI diagnostic imaging due to a greater adoption of the advanced medical imaging technologies.
Furthermore emerging countries in Asia Pacific will continue to grow at a moderate rate over the forecast period because of mounting healthcare infrastructure development healthcare expenditure and government support to provide healthcare solutions.
The AI-enabled diagnostic imaging market report is a compilation of first-hand information qualitative and quantitative assessment by industry analysts and inputs from industry experts and industry participants across the value chain.
The report provides in-depth analysis of parent market trends macro-economic indicators and governing factors along with market attractiveness as per segment. The market report also maps the qualitative impact of various market factors on market segments and geographies.
The report covers exhaustive analysis on:
- AI-enabled Diagnostic Imaging Market Segments
- AI-enabled Diagnostic Imaging Market Dynamics
- AI-enabled Diagnostic Imaging Market Size
- Supply & Demand
- Current Trends/Issues/Challenges
- Competition & Companies Involved in the Market
- Technology Landscape
- Value Chain of the Market
- Market Drivers and Restraints
Regional analysis includes:
- North America (U.S. Canada)
- Latin America (Mexico Brazil Rest of LATAM)
- Europe (Germany Italy U.K Spain France Nordic countries BENELUX Russia Rest of Europe)
- East Asia (China Japan South Korea)
- South Asia and Pacific (India Malaysia Indonesia Singapore Australia & New Zealand Rest of South Asia and Pacific)
- Middle East and Africa (GCC Countries Turkey Northern Africa South Africa Rest of MEA)
- Detailed overview of parent AI-enabled Diagnostic Imaging market
- Changing AI-enabled Diagnostic Imaging market dynamics in the industry
- In-depth market segmentation
- Historical current and projected market size in terms of value
- Recent industry trends and developments
- Competitive landscape of AI-enabled Diagnostic Imaging Market
- Strategies of key players and products offered
- Potential and niche segments geographical regions exhibiting promising growth
- A neutral perspective on market performance
- Must-have information for market players to sustain and enhance their market footprint
AI-enabled Diagnostic Imaging Market: Segmentation
The AI-enabled diagnostic imaging market can be segmented on the basis of solution, AI technology, End-user, Image acquisition technology, and region.
- Software Tools/Platforms
- Professional Services
- Managed Services
- Deep Learning
- Machine Learning
- Computer Vision
- R&D centers
- Laboratories and Diagnostic centers
- Computed Tomography
- Magnetic Resonance Imaging
- Ultrasound Imaging
- Molecular Imaging
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