Artificial Intelligence (AI) is a branch of science related to computer systems that can perform tasks that normally require human Intelligence. AI uses analytical models and digital inputs to gather large streams of data. AI models can then quickly process this data and react with human-like intelligence. Some AI technology uses Deep Learning and Machine Learning to constantly learn and develop its knowledge. AI-driven technologies are expected to replace enterprise software. Currently, AI has impacted almost every industry sector. On the software side, there will soon be more sophisticated Artificial Intelligence-based platforms as technology trends towards platforms becoming open-sourced. Today’s Artificial Intelligence is called Narrow or Weak AI, since it can perform simple tasks (e.g., facial recognition, internet searches, or driving a car). Although AI technologies have not yet reached their full potential, Narrow AI is already present in cars, internet search engines, Amazon.com shopping suggestions, and many other devices.
All industries use some form of AI devices, but the healthcare industry is expected to use AI technology the most. AI healthcare is often used for things like patient care, drug discovery, and personalized treatment. Artificial Intelligence can review an image and identify potential findings within it by searching a patient’s history related to the particular anatomy scanned.
AI is unlikely to replace radiologists anytime soon, but it will increase the value they provide. In most countries there are not enough radiologists to meet the growing demand for imaging and diagnostic healthcare services. This shortage is expected to get worse in future: as imaging services grow, the population ages and chronic diseases grow faster than new radiologists are entering the field. AI algorithms read medical images by identifying patterns within the image the way radiologists do. AI systems are trained to recognize normal anatomy through typical scans from CT, magnetic resonance imaging (MRI), ultrasound or nuclear imaging. Knowledge regarding the automated analysis of medical images has spread rapidly, though the impact of AI on the radiology field will probably occur gradually.
The global Artificial Intelligence market is projected to reach approximately $139 billion by 2027. This would be an increase from $8.2 billion in 2013, at a growth rate of 40 percent from 2017 to 2027. Advancements in image and voice recognition technology are critical to offering enhanced drones, self-driving cars, and robotics, thus promoting the expansion of the Artificial Intelligence market.
Global investment for Artificial Intelligence has come from three different sources:
- direct investment by industrial and IT companies,
- acquisition and development of small,established AI companies
- venture capital funding of AI startups.
In 2016, the overall global investment in Artificial Intelligence was more than $5 billion an increase of more than 60 percent over 2015. In 2015, the investments are estimated to be roughly $3.1 billion, or 6 percent of total VC investments that totaled $55 billion in 2015.
In 2016, the global diagnostic imaging equipment market was valued at $22.7 billion at a growth rate of 2 percent. X-rays are the most common diagnostics imaging tool used worldwide, while PET and PET-CT scanning are widely considered the best. The medical imaging and diagnostics industry has become saturated with companies in recent years compared to other Artificial Intelligence application area in the healthcare industry. Nineteen out of the 24 imaging & diagnostics companies raised their first equity funding round since January 2015. (This includes seed or Series A rounds, as well as a first-round raised by stealth startup Imagen Technologies.)
Deep Learning (DL) is a subset of AI that is stimulated by the working of human brain. Deep Learning algorithms can help clinicians and radiologists diagnose diseases and plan treatments. Deep Learning is making rapid advances in diagnostic radiology. It is estimated that the total global computer-aided diagnostics software market could be worth $16 billion. In 2016 the market was valued at $1 billion, and the progression in medical software businesses and imaging device companies could average 20-35 percent growth rate per year. This will continue as Deep Learning improves their throughput and generates new products and services in coming decade.
The current business strategy among many large companies in diagnostic imaging is to leverage licensing agreements and work collaboratively with technology suppliers, rather than to acquire these companies outright. In order to make up for the lack of commercial funding available from traditional venture capital resources for imaging technology, most of the key imaging OEM’s have established corporate venture funds. For example, Siemens Venture Capital Healthcare, Philips Healthcare Incubator, and the GE Healthymagination Fund.
Philips is the most active assignee in the year 2017. Most of the patents of Philips during the year 2017 focus on the devices which can be used for medical imaging. Philips has the priority filing in USA in this year. Apart from Philips, Siemens has been the second most active assignee in the domain in the year 2017.
The growth of the global Artificial Intelligence market is directly correlated with prevailing economic conditions across the globe. The rising level of disposable income has propelled the spending trends on healthcare. In addition, the improving global economy is expected to take a step further in the years ahead and catalyze the growth of AI in healthcare industry. Artificial Intelligence technologies will be quickly assimilated into analytics practices, providing consumers exceptional access to powerful insights that drive action. To improve, the healthcare industry is currently in need of Artificial Intelligence to provide knowledgeable, actionable insights from large sets of patient data and to create a unified informatics architecture.
An important trend in diagnostic medical imaging is a growing interest in fusion and multimodality imaging. As the market for diagnostic imaging equipment matures, new opportunities are emerging for imaging modalities that can be used by mobile doctors or health-care workers in the field. Another major trend is the idea of smaller, portable imaging machineries. The global medical imaging market is facing increasing competition from refurbished systems due to the high cost of devices and installation in developing markets.
IBM/Merge, Philips, Agfa, and Siemens have already started incorporating AI into their medical imaging software systems. The implementation of AI technology into medical imaging has particular challenges:
- diagnoses are not always confirmed
- classifications and concepts are not always unanimous, nor are they eternal
- the structures of the human body present great variation in terms of normal dimensions and textures, and this variation potentially masks pathological conditions
Key questions answered and insights delivered in the report:
- Global Artificial Intelligence market size; 2014-2027.
- Global Artificial Intelligence market by investment; 2014-2017.
- Global Artificial Intelligence market by M&A deals; 2014-2027.
- Global Artificial Intelligence M&A deals share by country; 2016.
- Global Artificial Intelligence market by technology; 2017.
- Global Artificial Intelligence market by applications; 2014-2027.
- Global Artificial Intelligence market by regions; 2027.
- Global Artificial Intelligence in healthcare market; 2014-2027.
- Global Artificial Intelligence in healthcare by application; 2014-2027.
- Top 10 use cases of Artificial Intelligence in healthcare; 2027.
- Global Artificial Intelligence in healthcare by companies; 2014-2027.
- US Artificial Intelligence in healthcare market; 2013-2027.
- US Artificial Intelligence in healthcare by application; 2017-2020.
- Europe Artificial Intelligence in healthcare market; 2016-2027.
- Australia Artificial Intelligence in healthcare market; 2016-2027.
- Japan Artificial Intelligence in medical and welfare market size; 2015-2027.
- Global Medical Imaging Market Value by Modality; 2007-2016
- US Medical Imaging Market Value by Modality; 2008
- Canada Diagnostic Imaging Equipment Market Growth Rate; 2008-2015
- Canada Diagnostic Imaging Equipment Market Growth Rate; 2008-2015
- Global Artificial Intelligence Market by Companies; 2010-2016
- Global Artificial Intelligence in Medical Imaging by Application; 2010-2016
- Global Artificial Intelligence in Medical Imaging by Funding; 2014-Q1 2017
- Top 15 Most Funded Companies in Artificial Intelligence in Medical Imaging; 2014-Q1 2017
- Global Computer Aided Diagnostic Market by Value; 2016-2022
- Comparison of Deep Learning Results with Human Radiologist and Conventional Computer Vision System
- Current healthcare regulations related to software in the European Union & US.
- Overall IP Trends in Artificial Intelligence in Medical Imaging Market; 2012-2017.
- Earliest Priority Country Filing Trend in Artificial Intelligence in Medical Imaging Market; 2012-2017
- Artificial Intelligence in Medical Imaging Patent Trends by Focus Area; 2012-2017
- Artificial Intelligence in Healthcare Patent Trends by Application; 2012-2017
- Key Patents in Artificial Intelligence in Medical Imaging
- Key Patent Holders in Artificial Intelligence in Medical Imaging Market; 2012-2017
- Top Inventors in Artificial Intelligence in Medical Imaging Market; 2017
- Top Active Inventors Associated with the Key Players in Artificial Intelligence in Medical Imaging Market
- Competitive landscape of Artificial Intelligence players in Medical Imaging market.
- Comprehensive product analysis of Artificial Intelligence in Medical Imaging market.
- Detailed analysis of growth drivers, challenges and trends in Artificial Intelligence in Medical Imaging market.
- Detailed company profiling of key market players: Microsoft, IBM, Google, iCarbonX, Deep Genomics, Nvidia, Butterfly Network, Flatiron Health, Welltok, BenevolentAI, Philips, Siemens and Zephyr Health.
Executive Summary
Key Questions Answered
1. An Introduction: Artificial Intelligence
I. Different Stages of Artificial Intelligence
II. History of Artificial Intelligence
III. Applications of Artificial Intelligence
a. Healthcare
b. Education
c. Finance
d. Law
e. Manufacturing
f. Marketing
2. Artificial Intelligence in Healthcare
I. Artificial Intelligence in Medical Imaging
a. Deep Learning in Medical Imaging
II. Applications of AI in Medical Imaging Market
a. Radiologists
b. Clinicians
c. Back Office Workspan>
d. Clinical Research and Education
3. Unmet Clinical Demand
I. Healthcare Professionals Shortage
a. Physicians
b. Nurses and Midwives
c. Other Cadres
II. Misdiagnosis
III. Shortage of Radiologists
4. Impact of AI on Medical Innovation in the European Union & US
I. Current Regulation of Software in the European Union
II. European Union Regulation of Software under the New Medical Device Regulations
a. Data Protection and Cybersecurity Implications
III. Current Regulation of Software in the United States
a. Data Protection and Privacy Issues
b. Cybersecurity and Quality Control Implications
5. Artificial Intelligence Market Size
I. Global Artificial Intelligence Market
II. Global Artificial Intelligence Market by Investment
III. Global Artificial Intelligence Market by M&A Deals
IV. Global Artificial Intelligence Market by Technology
V. Global Artificial Intelligence Market by Application & Use Cases
VI. Global Artificial Intelligence Market by Region
6. Artificial Intelligence in Healthcare Market Size
I. Global Artificial Intelligence in Healthcare Market
II. Global Artificial Intelligence in Healthcare Market by Application
a. Robot-Assisted Surgery
Top 10 Companies in Robot-assisted Surgery
Case Study of Smart Tissue Autonomous Robot (STAR) Soft Tissue Surgery
b. Virtual Nursing Assistants
Sense.ly Virtual Nurse Assistance Molly & Alme Health Coach
c. Administrative Workflow Assistant
III. Global Artificial Intelligence in Healthcare Market by Companies
IV. The US Artificial Intelligence in Healthcare Market
V. Europe Artificial Intelligence in Healthcare Market
VI. Australia Artificial Intelligence in Healthcare Market
Diabetic Retinopathy Case in Australia
VII. Japan Artificial Intelligence in Healthcare Market
7. Artificial Intelligence in Medical Imaging Market
I. Global Diagnostic Imaging Equipment Market
II. US Medical Imaging Equipment Market
III. Canada Medical Imaging Equipment Market
IV. Artificial Intelligence in Medical Imaging Market: Actual & Forecast
V. Deep Learning in Medical Imaging Market: Actual & Forecast
8. Competitive Landscape
9. Product Analysis
I. AI Medical Imaging Device / Software in Healthcare Market
10. Patent Landscape
I. Overall IP Trends in Artificial Intelligence in Medical Imaging Market
II. Artificial Intelligence in Medical Imaging Patent Trends by Focus Area
III. Artificial Intelligence in Medical Imaging Patent Trends by Application
IV. Key Patents in Artificial Intelligence in Medical Imaging Market
V. Artificial Intelligence in Medical Imaging Patent Trends by Key Players (Legal Assignees)
a. Top Collaborations of the Assignees
VI. Artificial Intelligence in Medical Imaging Patent Trends by Top Inventors
11. Growth Drivers
I. Accelerating Economic Growth
II. Increasing Healthcare Expenditure
III. Increasing Healthcare Data
IV. Growth in Cloud Computing Infrastructures & Big Data
V. Growing Insights-Driven Market
12. Trends
I. Fusion/Multimodality
II. Portable Imaging Equipment
III. Growing Refurbished Medical Imaging Market
IV. Cost Savings through Software
13. Challenges
I. Availability of Structured and Standardized Data
II. Eating Away Jobs
III. Patient Hesitation
IV. Data Security
14. Company Profiling
I. Microsoft
a. Business Overview
b. Financial Overview
c. AI Products / Services
II. International Business Machines Corporation (IBM Watson)
a. Business Overview
b. Financial Overview
c. AI Products / Services
d. Collaborations
III. Google (DeepMind)
a. Business Overview
b. Financial Overview
c. AI Products / Services
d. Collaborations
IV. MedyMatch Technology
a. Business Overview
b. Financial Overview
c. AI Products / Services
d. M&A Activity
V. iCarbonX
a. Business Overview
b. Financial Overview
c. AI Products / Services
d. M&A Activity
VI. Deep Genomics
a. Business Overview
b. Financial Overview
VII. Nvidia
a. Business Overview
b. Financial Overview
c. AI Products / Services
VIII. Butterfly Network
a. Business Overview
b. Financial Overview
c. AI Products / Services
IX. Flatiron Health
a. Business Overview
b. Financial Overview
c. AI Products / Services
X. Welltok
a. Business Overview
b. Financial Overview
c. AI Products / Services
d. M&A Activities
XI. BenevolentAI
a. Business Overview
b. Financial Overview
c. Collaborations
XII. Zephyr Health
a. Business Overview
b. Financial Overview
c. AI Products / Services
XIII. Philips Healthcare
a. Business Overview
b. Financial Overview
c. AI Products / Services
d. Collaborations
XIV. Siemens Healthcare
a. Business Overview
b. Financial Overview
c. AI Products / Services
About Us
Disclaimer
Fig 1.1 Multiple Areas Involved in Artificial Intelligence
Fig 1.2 Different Stages of Artificial Intelligence
Fig 1.3 History of Artificial Intelligence
Fig 1.4 Adoption of Artificial Intelligence by Industry
Fig 2.1 Image Classification Error Rate; 2010-2016
Fig 3.1 Global Health Worker Needs-based Shortages; 2013-2030
Fig 3.2 Radiologist per 1000 people by Country; 2008
Fig 5.1 Global Artificial Intelligence Market by Value; 2014-2027
Fig 5.2 Global Artificial Intelligence Market by Investment (Disclosed Funding); 2014-2017
Fig 5.3 Global Artificial Intelligence Market by M&A Deals; 2014-2017
Fig 5.4 Global Artificial Intelligence Deals Share by Country; 2016
Fig 5.5 Global Artificial Intelligence Market by Technology; 2017
Fig 5.6 Global Artificial Intelligence Market by Application; 2014-2027
Fig 5.7 Top 10 Use Cases of Artificial Intelligence; 2027
Fig 5.8 Global Artificial Intelligence Market by Region; 2027
Fig 5.9 Global Artificial Intelligence Growth Rate by Region; 2015-2020
Fig 6.1 Global Artificial Intelligence in Healthcare Market by Value; 2014-2027
Fig 6.2 Global Artificial Intelligence in Healthcare Market by Application by Value; 2027
Fig 6.3 Global Artificial Intelligence in Healthcare Market by Companies; 2027
Fig 6.4 US Artificial Intelligence in Healthcare Market by Value; 2013-2027
Fig 6.5 US Artificial Intelligence in Healthcare Market by Application by Value; 2017-2020
Fig 6.6 Europe Artificial Intelligence in Healthcare Market by Value; 2016-2027
Fig 6.7 Australia Artificial Intelligence in Healthcare Market by Value; 2016-2027
Fig 6.8 Japan Artificial Intelligence in Medical & Welfare Market by Value; 2015-2027
Fig 7.1 Global Medical Imaging Market Value by Modality; 2007-2016
Fig 7.2 US Medical Imaging Market Value by Modality; 2008
Fig 7.3 Canada Diagnostic Imaging Equipment Market Growth Rate; 2008-2015
Fig 7.4 Global Artificial Intelligence in Medical Imaging Market by Companies; 2010-2016
Fig 7.5 Global Artificial Intelligence in Medical Imaging by Application; 2010-2016
Fig 7.6 Global Artificial Intelligence in Medical Imaging by Funding; 2014-Q1 2017
Fig 7.7 Top 15 Most Funded Companies in Artificial Intelligence in Medical Imaging; 2014-Q1 2017
Fig 7.8 Global Computer Aided Diagnostic Market by Value; 2016-2022
Fig 7.9 Comparison of Deep Learning Results with Human Radiologist and Conventional Computer Vision System
Fig 10.1: Overall IP Trends in Artificial Intelligence in Medical Imaging Market; 2012-2018
Fig 10.2: Earliest Priority Country Filing Trend in Artificial Intelligence in Medical Imaging Market; 2012-2018
Fig 10.3: Main Patent Focus in Artificial Intelligence in Medical Imaging Market; 2012-2018
Fig 10.4: Main Patent Focus in Artificial Intelligence in Healthcare Market; 2012-2017
Fig 10.5: Key Patent Holders (Legal Assignees) in Artificial Intelligence in Medical Imaging Market; 2017
Fig 10.6: Top Inventors in Artificial Intelligence in Medical Imaging Market; 2017
Fig 11.1 Global GDP; 1990-2025
Fig 11.2 Global Healthcare Expenditure; 2012-2026
Fig 11.3 Global Healthcare Data; 2013-2026
Fig 11.4 Big Data Market Revenue; 2011-2017
Fig 11.5 Insights Driven Market by Value; 2015-2020
Fig 14.1 Microsoft Revenue by Products and Services; 2014-2017
Fig 14.2 Microsoft R&D Investment; 2014-2017
Fig 14.3 Microsoft Healthcare AI projects; 2017
Fig 14.4 IBM Revenue; 2012-2016
Fig 14.5 IBM R&D Investment; 2015-2016
Fig 14.6 Google Revenue; 2012-2016
Fig 14.7 Nvidia Revenue; 2013-2017
Fig 14.8 Nvidia R&D investment; 2013-2017
Fig 14.9 Philips Healthcare Revenue; 2014-2016
Fig 14.10 Philips Personal Healthcare Geographic Revenue; 2014-2016
Fig 14.11 Siemens Healthcare Revenue; 2013-2017
Table 6.1 Top 10 Companies in Robot-assisted Surgery
Table 8.1: Key Players in AI Medical Imaging Device / Software in Market
Table 9.1: AI Medical Imaging Device / Software in Healthcare Market
Table 10.1 Artificial Intelligence in Medical Imaging Patent Trends by Focus Area (Year Wise Filing); 2012-2018
Table 10.2 Artificial Intelligence in Medical Imaging in Patent Trends by Application (Year Wise Filing); 2012-2018
Table 10.3 Key Patents in Artificial Intelligence in Medical Imaging
Table 10.4 Key Patent Holders (Legal Assignees) Year Wise Patent Filing in Artificial Intelligence in Medical Imaging Market; 2012-2018
Table 10.5 Key Patent Holders (Legal Assignees) Patent Filing in Artificial Intelligence in Medical Imaging Market by Focus Area; 2012-2018
Table 10.6 Key Patent Holders (Legal Assignees) Patent Filing in Artificial Intelligence in Healthcare Market by Application; 2012-2018
Table 10.7 Top Active Inventors Associated with the Key Players in Artificial Intelligence in Medical Imaging Market
Table 14.1 Microsoft Healthcare AI Projects
Table 14.2 IBM Collaborations
Table 14.3 Google M&A Activities / Collaborations
Table 14.4 MedyMatch Technology M&A Deals
Table 14.5 iCarbonX Technology M&A Deals
Table 14.6 Butterfly iQ Product Description
Table 14.6 Welltok M&A Activities
Table 14.7 BenevolentAI Collaborations
Table 14.8 Phillips Collaborations