Market Overview:
The global machine learning in medical imaging market is expected to grow at a CAGR of 16.5% during the forecast period from 2018 to 2030. The growth of the market can be attributed to factors such as increasing demand for early diagnosis and treatment, rising prevalence of chronic diseases, and technological advancements in medical imaging devices. Based on type, the global machine learning in medical imaging market is segmented into supervised learning, unsupervised learning, semi-supervised learning, and reinforced learning. Supervised Learning is further sub-segmented into linear regression models and decision trees while unsupervised Learning is further sub-segmented into clustering algorithms and neural networks. In terms of application, the global machine learning in medical imaging market is segmented into breast cancer detection & diagnosis; lung cancer detection & diagnosis; neurology disorders such as Alzheimer’s disease detection & diagnosis; cardiovascular diseases such as heart attack prediction; liver cirrhosis detection & other liver diseases; other applications including ophthalmology image analysis etc.
Product Definition:
Machine learning is a process of teaching computers to learn from data, without being explicitly programmed. It is a type of artificial intelligence that allows computer systems to change and improve performance as they collect more data. In medical imaging, machine learning can be used to automatically detect and diagnose diseases in images such as X-rays, CT scans or MRI scans. Machine learning algorithms can also be used to predict the outcome of treatments or surgeries.
Supervised Learning:
Supervised learning is a type of machine learning that involves the training of an algorithm to learn from example data. In this method, the computer is given specific inputs and it reacts according to those inputs by producing an output. Supervised learning in medical imaging market has applications in image analysis and pattern recognition where the algorithms are used for diagnosis or detection or monitoring processes.
Unsupervised Learning:
Unsupervised learning is also known as data mining. It is a process of extracting information from data sets by using various techniques. Unsupervised learning helps in finding patterns or relationships among the data set and finds applications in medical imaging, computer vision, robotics, and automated image organization extraction (AIOps).
Application Insights:
The breast application segment dominated the market in 2017. This can be attributed to the high usage of machine learning algorithms for screening mammography images to reduce over-diagnosis and under-diagnosis. For instance, a study by National Cancer Center, Japan used Support Vector Machine (SVM) for image classification based on breast tissue characteristics in order to reduce over diagnosis and under diagnosis of breast cancer.
The lung application segment is expected to grow at a lucrative rate during the forecast period owing to increasing prevalence of chronic diseases such as asthma and COPD which are highly prevalent among millennials due smoking related causes such as air pollution exposure. For instance, an artificial intelligence system known as Lung AI was developed by researchers from Peking University for early detection of lung cancer using computerized tomography images taken after surgery patients have had their lungs removed.
Regional Analysis:
North America dominated the market in 2017 owing to the presence of a large number of players, increased adoption rate of advanced technologies and high healthcare expenditure. The region is expected to maintain its dominance over the forecast period due to continuous innovations in machine learning techniques for medical imaging. Asia Pacific is anticipated to grow at a lucrative CAGR during the forecast period due to increasing government initiatives for developing diagnostic systems and rising awareness about early diagnosis. Moreover, increasing investments by companies are likely ot boost growth further. For instance, In January 2018, Siemens Healthineers announced that it had developed new lung cancer screening technology based on artificial intelligence (AI) and deep learning with support from Google AI Residency Program’s Summer Scholar program 2016-2017 cohort in China (Shenzhen).
Growth Factors:
- Increasing demand for early diagnosis and treatment of diseases: The increasing demand for early diagnosis and treatment of diseases is one of the key growth drivers for the machine learning in medical imaging market. This is because machine learning helps in detecting the disease at an early stage, which helps in reducing its impact on the patient.
- Growing number of image-based diagnostic procedures: The growing number of image-based diagnostic procedures is another key growth driver for the machine learning in medical imaging market. This is because machine learning helps to improve accuracy and efficiency while performing these diagnostic procedures.
- Rising prevalence of chronic diseases: The rising prevalence of chronic diseases such as cancer, diabetes, and heart disease is another key growth driver for the machine learning in medical imaging market. This is becausemachinelearning can help to detect these diseases at an early stage, which can help to improve patient outcomes significantly .
Scope Of The Report
Report Attributes
Report Details
Report Title
Machine Learning in Medical Imaging Market Research Report
By Type
Supervised Learning, Unsupervised Learning, Semi Supervised Learning, Reinforced Leaning
By Application
Breast, Lung, Neurology, Cardiovascular, Liver, Others
By Companies
Zebra, Arterys, Aidoc, MaxQ AI, Google, Tencent, Alibaba
Regions Covered
North America, Europe, APAC, Latin America, MEA
Base Year
2021
Historical Year
2019 to 2020 (Data from 2010 can be provided as per availability)
Forecast Year
2030
Number of Pages
186
Number of Tables & Figures
131
Customization Available
Yes, the report can be customized as per your need.
Global Machine Learning in Medical Imaging Market Report Segments:
The global Machine Learning in Medical Imaging market is segmented on the basis of:
Types
Supervised Learning, Unsupervised Learning, Semi Supervised Learning, Reinforced Leaning
The product segment provides information about the market share of each product and the respective CAGR during the forecast period. It lays out information about the product pricing parameters, trends, and profits that provides in-depth insights of the market. Furthermore, it discusses latest product developments & innovation in the market.
Applications
Breast, Lung, Neurology, Cardiovascular, Liver, Others
The application segment fragments various applications of the product and provides information on the market share and growth rate of each application segment. It discusses the potential future applications of the products and driving and restraining factors of each application segment.
Some of the companies that are profiled in this report are:
- Zebra
- Arterys
- Aidoc
- MaxQ AI
- Google
- Tencent
- Alibaba
Highlights of The Machine Learning in Medical Imaging Market Report:
- The market structure and projections for the coming years.
- Drivers, restraints, opportunities, and current trends of market.
- Historical data and forecast.
- Estimations for the forecast period 2030.
- Developments and trends in the market.
- By Type:
- Supervised Learning
- Unsupervised Learning
- Semi Supervised Learning
- Reinforced Leaning
- By Application:
- Breast
- Lung
- Neurology
- Cardiovascular
- Liver
- Others
- Market scenario by region, sub-region, and country.
- Market share of the market players, company profiles, product specifications, SWOT analysis, and competitive landscape.
- Analysis regarding upstream raw materials, downstream demand, and current market dynamics.
- Government Policies, Macro & Micro economic factors are also included in the report.
We have studied the Machine Learning in Medical Imaging Market in 360 degrees via. both primary & secondary research methodologies. This helped us in building an understanding of the current market dynamics, supply-demand gap, pricing trends, product preferences, consumer patterns & so on. The findings were further validated through primary research with industry experts & opinion leaders across countries. The data is further compiled & validated through various market estimation & data validation methodologies. Further, we also have our in-house data forecasting model to predict market growth up to 2030.
Regional Analysis
- North America
- Europe
- Asia Pacific
- Middle East & Africa
- Latin America
Note: A country of choice can be added in the report at no extra cost. If more than one country needs to be added, the research quote will vary accordingly.
The geographical analysis part of the report provides information about the product sales in terms of volume and revenue in regions. It lays out potential opportunities for the new entrants, emerging players, and major players in the region. The regional analysis is done after considering the socio-economic factors and government regulations of the countries in the regions.
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8 Reasons to Buy This Report
- Includes a Chapter on the Impact of COVID-19 Pandemic On the Market
- Report Prepared After Conducting Interviews with Industry Experts & Top Designates of the Companies in the Market
- Implemented Robust Methodology to Prepare the Report
- Includes Graphs, Statistics, Flowcharts, and Infographics to Save Time
- Industry Growth Insights Provides 24/5 Assistance Regarding the Doubts in the Report
- Provides Information About the Top-winning Strategies Implemented by Industry Players.
- In-depth Insights On the Market Drivers, Restraints, Opportunities, and Threats
- Customization of the Report Available
Frequently Asked Questions?
Machine learning is a subset of artificial intelligence that uses algorithms to improve the performance of predictive models. Predictive models are used to identify patterns in data and use that information to make predictions about future events or outcomes. Machine learning can be used in medical imaging applications to improve the accuracy and speed of image analysis, diagnosis, and treatment planning.
Some of the major companies in the machine learning in medical imaging market are Zebra, Arterys, Aidoc, MaxQ AI, Google, Tencent, Alibaba.
The machine learning in medical imaging market is expected to register a CAGR of 16.5%.
Chapter 1 Executive Summary
Chapter 2 Assumptions and Acronyms Used
Chapter 3 Research Methodology
Chapter 4 Machine Learning in Medical Imaging Market Overview
4.1 Introduction
4.1.1 Market Taxonomy
4.1.2 Market Definition
4.1.3 Macro-Economic Factors Impacting the Market Growth
4.2 Machine Learning in Medical Imaging Market Dynamics
4.2.1 Market Drivers
4.2.2 Market Restraints
4.2.3 Market Opportunity
4.3 Machine Learning in Medical Imaging Market - Supply Chain Analysis
4.3.1 List of Key Suppliers
4.3.2 List of Key Distributors
4.3.3 List of Key Consumers
4.4 Key Forces Shaping the Machine Learning in Medical Imaging Market
4.4.1 Bargaining Power of Suppliers
4.4.2 Bargaining Power of Buyers
4.4.3 Threat of Substitution
4.4.4 Threat of New Entrants
4.4.5 Competitive Rivalry
4.5 Global Machine Learning in Medical Imaging Market Size & Forecast, 2018-2028
4.5.1 Machine Learning in Medical Imaging Market Size and Y-o-Y Growth
4.5.2 Machine Learning in Medical Imaging Market Absolute $ Opportunity
Chapter 5 Global Machine Learning in Medical Imaging Market Analysis and Forecast by Type
5.1 Introduction
5.1.1 Key Market Trends & Growth Opportunities by Type
5.1.2 Basis Point Share (BPS) Analysis by Type
5.1.3 Absolute $ Opportunity Assessment by Type
5.2 Machine Learning in Medical Imaging Market Size Forecast by Type
5.2.1 Supervised Learning
5.2.2 Unsupervised Learning
5.2.3 Semi Supervised Learning
5.2.4 Reinforced Leaning
5.3 Market Attractiveness Analysis by Type
Chapter 6 Global Machine Learning in Medical Imaging Market Analysis and Forecast by Applications
6.1 Introduction
6.1.1 Key Market Trends & Growth Opportunities by Applications
6.1.2 Basis Point Share (BPS) Analysis by Applications
6.1.3 Absolute $ Opportunity Assessment by Applications
6.2 Machine Learning in Medical Imaging Market Size Forecast by Applications
6.2.1 Breast
6.2.2 Lung
6.2.3 Neurology
6.2.4 Cardiovascular
6.2.5 Liver
6.2.6 Others
6.3 Market Attractiveness Analysis by Applications
Chapter 7 Global Machine Learning in Medical Imaging Market Analysis and Forecast by Region
7.1 Introduction
7.1.1 Key Market Trends & Growth Opportunities by Region
7.1.2 Basis Point Share (BPS) Analysis by Region
7.1.3 Absolute $ Opportunity Assessment by Region
7.2 Machine Learning in Medical Imaging Market Size Forecast by Region
7.2.1 North America
7.2.2 Europe
7.2.3 Asia Pacific
7.2.4 Latin America
7.2.5 Middle East & Africa (MEA)
7.3 Market Attractiveness Analysis by Region
Chapter 8 Coronavirus Disease (COVID-19) Impact
8.1 Introduction
8.2 Current & Future Impact Analysis
8.3 Economic Impact Analysis
8.4 Government Policies
8.5 Investment Scenario
Chapter 9 North America Machine Learning in Medical Imaging Analysis and Forecast
9.1 Introduction
9.2 North America Machine Learning in Medical Imaging Market Size Forecast by Country
9.2.1 U.S.
9.2.2 Canada
9.3 Basis Point Share (BPS) Analysis by Country
9.4 Absolute $ Opportunity Assessment by Country
9.5 Market Attractiveness Analysis by Country
9.6 North America Machine Learning in Medical Imaging Market Size Forecast by Type
9.6.1 Supervised Learning
9.6.2 Unsupervised Learning
9.6.3 Semi Supervised Learning
9.6.4 Reinforced Leaning
9.7 Basis Point Share (BPS) Analysis by Type
9.8 Absolute $ Opportunity Assessment by Type
9.9 Market Attractiveness Analysis by Type
9.10 North America Machine Learning in Medical Imaging Market Size Forecast by Applications
9.10.1 Breast
9.10.2 Lung
9.10.3 Neurology
9.10.4 Cardiovascular
9.10.5 Liver
9.10.6 Others
9.11 Basis Point Share (BPS) Analysis by Applications
9.12 Absolute $ Opportunity Assessment by Applications
9.13 Market Attractiveness Analysis by Applications
Chapter 10 Europe Machine Learning in Medical Imaging Analysis and Forecast
10.1 Introduction
10.2 Europe Machine Learning in Medical Imaging Market Size Forecast by Country
10.2.1 Germany
10.2.2 France
10.2.3 Italy
10.2.4 U.K.
10.2.5 Spain
10.2.6 Russia
10.2.7 Rest of Europe
10.3 Basis Point Share (BPS) Analysis by Country
10.4 Absolute $ Opportunity Assessment by Country
10.5 Market Attractiveness Analysis by Country
10.6 Europe Machine Learning in Medical Imaging Market Size Forecast by Type
10.6.1 Supervised Learning
10.6.2 Unsupervised Learning
10.6.3 Semi Supervised Learning
10.6.4 Reinforced Leaning
10.7 Basis Point Share (BPS) Analysis by Type
10.8 Absolute $ Opportunity Assessment by Type
10.9 Market Attractiveness Analysis by Type
10.10 Europe Machine Learning in Medical Imaging Market Size Forecast by Applications
10.10.1 Breast
10.10.2 Lung
10.10.3 Neurology
10.10.4 Cardiovascular
10.10.5 Liver
10.10.6 Others
10.11 Basis Point Share (BPS) Analysis by Applications
10.12 Absolute $ Opportunity Assessment by Applications
10.13 Market Attractiveness Analysis by Applications
Chapter 11 Asia Pacific Machine Learning in Medical Imaging Analysis and Forecast
11.1 Introduction
11.2 Asia Pacific Machine Learning in Medical Imaging Market Size Forecast by Country
11.2.1 China
11.2.2 Japan
11.2.3 South Korea
11.2.4 India
11.2.5 Australia
11.2.6 South East Asia (SEA)
11.2.7 Rest of Asia Pacific (APAC)
11.3 Basis Point Share (BPS) Analysis by Country
11.4 Absolute $ Opportunity Assessment by Country
11.5 Market Attractiveness Analysis by Country
11.6 Asia Pacific Machine Learning in Medical Imaging Market Size Forecast by Type
11.6.1 Supervised Learning
11.6.2 Unsupervised Learning
11.6.3 Semi Supervised Learning
11.6.4 Reinforced Leaning
11.7 Basis Point Share (BPS) Analysis by Type
11.8 Absolute $ Opportunity Assessment by Type
11.9 Market Attractiveness Analysis by Type
11.10 Asia Pacific Machine Learning in Medical Imaging Market Size Forecast by Applications
11.10.1 Breast
11.10.2 Lung
11.10.3 Neurology
11.10.4 Cardiovascular
11.10.5 Liver
11.10.6 Others
11.11 Basis Point Share (BPS) Analysis by Applications
11.12 Absolute $ Opportunity Assessment by Applications
11.13 Market Attractiveness Analysis by Applications
Chapter 12 Latin America Machine Learning in Medical Imaging Analysis and Forecast
12.1 Introduction
12.2 Latin America Machine Learning in Medical Imaging Market Size Forecast by Country
12.2.1 Brazil
12.2.2 Mexico
12.2.3 Rest of Latin America (LATAM)
12.3 Basis Point Share (BPS) Analysis by Country
12.4 Absolute $ Opportunity Assessment by Country
12.5 Market Attractiveness Analysis by Country
12.6 Latin America Machine Learning in Medical Imaging Market Size Forecast by Type
12.6.1 Supervised Learning
12.6.2 Unsupervised Learning
12.6.3 Semi Supervised Learning
12.6.4 Reinforced Leaning
12.7 Basis Point Share (BPS) Analysis by Type
12.8 Absolute $ Opportunity Assessment by Type
12.9 Market Attractiveness Analysis by Type
12.10 Latin America Machine Learning in Medical Imaging Market Size Forecast by Applications
12.10.1 Breast
12.10.2 Lung
12.10.3 Neurology
12.10.4 Cardiovascular
12.10.5 Liver
12.10.6 Others
12.11 Basis Point Share (BPS) Analysis by Applications
12.12 Absolute $ Opportunity Assessment by Applications
12.13 Market Attractiveness Analysis by Applications
Chapter 13 Middle East & Africa (MEA) Machine Learning in Medical Imaging Analysis and Forecast
13.1 Introduction
13.2 Middle East & Africa (MEA) Machine Learning in Medical Imaging Market Size Forecast by Country
13.2.1 Saudi Arabia
13.2.2 South Africa
13.2.3 UAE
13.2.4 Rest of Middle East & Africa (MEA)
13.3 Basis Point Share (BPS) Analysis by Country
13.4 Absolute $ Opportunity Assessment by Country
13.5 Market Attractiveness Analysis by Country
13.6 Middle East & Africa (MEA) Machine Learning in Medical Imaging Market Size Forecast by Type
13.6.1 Supervised Learning
13.6.2 Unsupervised Learning
13.6.3 Semi Supervised Learning
13.6.4 Reinforced Leaning
13.7 Basis Point Share (BPS) Analysis by Type
13.8 Absolute $ Opportunity Assessment by Type
13.9 Market Attractiveness Analysis by Type
13.10 Middle East & Africa (MEA) Machine Learning in Medical Imaging Market Size Forecast by Applications
13.10.1 Breast
13.10.2 Lung
13.10.3 Neurology
13.10.4 Cardiovascular
13.10.5 Liver
13.10.6 Others
13.11 Basis Point Share (BPS) Analysis by Applications
13.12 Absolute $ Opportunity Assessment by Applications
13.13 Market Attractiveness Analysis by Applications
Chapter 14 Competition Landscape
14.1 Machine Learning in Medical Imaging Market: Competitive Dashboard
14.2 Global Machine Learning in Medical Imaging Market: Market Share Analysis, 2019
14.3 Company Profiles (Details – Overview, Financials, Developments, Strategy)
14.3.1 Zebra
14.3.2 Arterys
14.3.3 Aidoc
14.3.4 MaxQ AI
14.3.5 Google
14.3.6 Tencent
14.3.7 Alibaba
