Germany Artificial Intelligence in Healthcare Market Report 2022 to 2030

Germany Artificial Intelligence (AI) in Healthcare Market Analysis

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Germany's Artificial Intelligence (AI) in the healthcare market is projected to grow from $0.25 Bn in 2022 to $4.52 Bn by 2030, registering a CAGR of 43.42% during the forecast period of 2022-30. The market will be driven by the country's excellent research and development capabilities, well-established healthcare infrastructure, and favorable government policies. The market is segmented by healthcare components & by healthcare applications. Some of the major players include Google Health, NVIDIA Corporation, Semalytix & Smart Reporting.

ID: IN10DEDH003 CATEGORY: Digital Health GEOGRAPHY: Germany AUTHOR: Vidhi Upadhyay

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Germany Artificial Intelligence (AI) in Healthcare Market Executive Summary

Germany's Artificial Intelligence (AI) in healthcare market is projected to grow from $0.25 Bn in 2022 to $4.52 Bn by 2030, registering a CAGR of 43.42% during the forecast period of 2022-30. Germany has the world's third-largest medical technology industry, after only the United States and Japan, and it is also the largest European enterprise, with a market value that is double that of France and three times that of Italy, the United Kingdom, and Spain. Apart from the significant mortality burden caused by cardiovascular illnesses and lung cancer, musculoskeletal issues, dementias, and mental health problems (including depression) are some of the primary contributors to disability-related mortality. Germany has lost adjusted life years 2 (DALYs).

Some of the country's AI-related R&D centers:

DFKI (Das Deutsche Forschungszentrum für Künstliche Intelligenz GmbH)
Intelligent Analysis and Information Systems (IAIS)
Fraunhofer Institute for Medical Image Computing (MEVIS), and
Cyber Valley

The country is working to establish supra-regional Centers of Excellence for AI in order to provide new AI services globally. Artificial intelligence (AI) is gaining traction in healthcare in Germany, with an increasing number of enterprises and organizations such as DiaMonTech, Mika, TeleClinic, & Ada Health who are adopting and deploying AI-based solutions to improve patient outcomes and expedite healthcare delivery. In May 2022, India and Germany agreed to collaborate on AI start-ups as well as AI research and its applications in sustainability and healthcare. AI has the potential to revolutionize German healthcare by boosting diagnosis accuracy, optimizing treatment programs, and minimizing medical errors.

germany artificial intelligence in healthcare market

Market Dynamics

Market Growth Drivers

The country's excellent research and development capabilities, well-established healthcare infrastructure, and favorable government policies fostering digitization and innovation in healthcare are among the major factors for AI in healthcare in Germany. Furthermore, Germany's aging population has resulted in an increase in demand for healthcare services, which AI-powered solutions can assist to address. Furthermore, the COVID-19 pandemic had highlighted the need for more efficient and effective healthcare systems, which AI-enabled remote monitoring and telemedicine are helping to achieve.

Market Restraints

there are various barriers to AI adoption in healthcare in Germany. One of the main concerns is data privacy and security, which is a huge issue in Germany due to the rigorous data protection laws in place. This can make accessing and analyzing the massive amounts of medical data required to train AI models difficult. Furthermore, there is a disparity in data gathering and sharing across healthcare providers, making integration of AI systems into existing healthcare infrastructure complicated. Also, there is a scarcity of skilled AI professionals, and more training programs are needed to build the requisite knowledge in this subject. Finally, guidelines are required to assure the safety and effectiveness of AI-enabled healthcare solutions. As a result, addressing these difficulties and promoting the appropriate use of AI for the benefit of patients and society as a whole will necessitate collaboration between the government, healthcare providers, and technology businesses in Germany.

Competitive Landscape

Key Players

IBM Watson Health
Google Health
NVIDIA Corporation
GE Healthcare
Philips Healthcare
Siemens Healthineers
Semalytix (DEU)
Smart Reporting (DEU)
DiaMonTech (DEU)
Mika (DEU)
TeleClinic (DEU)
Aignostics (DEU)
Vara (DEU)
Nostos Genomics (DEU)

Notable Insights

February 2023, GE HealthCare to Acquire Caption Health The acquisition adds AI-enabled image guiding to the ultrasound device portfolios of GE HealthCare's $3 billion Ultrasound division
In May 2022, India and Germany agreed to collaborate on AI start-ups as well as AI research and its applications in sustainability and healthcare

1. Executive Summary
1.1 Digital Health Overview
1.2 Global Scenario
1.3 Country Overview
1.4 Healthcare Scenario in Country
1.5 Digital Health Policy in Country
1.6 Recent Developments in the Country

2. Market Size and Forecasting
2.1 Market Size (With Excel and Methodology)
2.2 Market Segmentation (Check all Segments in Segmentation Section)

3. Market Dynamics
3.1 Market Drivers
3.2 Market Restraints

4. Competitive Landscape
4.1 Major Market Share

4.2 Key Company Profile (Check all Companies in the Summary Section)

4.2.1 Company
4.2.1.1 Overview
4.2.1.2 Product Applications and Services
4.2.1.3 Recent Developments
4.2.1.4 Partnerships Ecosystem
4.2.1.5 Financials (Based on Availability)

5. Reimbursement Scenario
5.1 Reimbursement Regulation
5.2 Reimbursement Process for Diagnosis
5.3 Reimbursement Process for Treatment

6. Methodology and Scope

Germany Artificial Intelligence (AI) in Healthcare Market Segmentation

By Healthcare Component (Revenue, USD Billion):

Software Solutions
Hardware
Services

By Healthcare Applications (Revenue, USD Billion):

Robot-Assisted Suregery
Virtual Assistants
Administrative Workflow Assistants
Connected Machines
Diagnosis
Clinical Trials
Fraud Detection
Cybersecurity
Dosage Error Reduction

Methodology for Database Creation

Our database offers a comprehensive list of healthcare centers, meticulously curated to provide detailed information on a wide range of specialties and services. It includes top-tier hospitals, clinics, and diagnostic facilities across 30 countries and 24 specialties, ensuring users can find the healthcare services they need.

Additionally, we provide a comprehensive list of Key Opinion Leaders (KOLs) based on your requirements. Our curated list captures various crucial aspects of the KOLs, offering more than just general information. Whether you're looking to boost brand awareness, drive engagement, or launch a new product, our extensive list of KOLs ensures you have the right experts by your side. Covering 30 countries and 36 specialties, our database guarantees access to the best KOLs in the healthcare industry, supporting strategic decisions and enhancing your initiatives.

How Do We Get It?

Our database is created and maintained through a combination of secondary and primary research methodologies.

1. Secondary Research

With many years of experience in the healthcare field, we have our own rich proprietary data from various past projects. This historical data serves as the foundation for our database. Our continuous process of gathering data involves:

Analyzing historical proprietary data collected from multiple projects.
Regularly updating our existing data sets with new findings and trends.
Ensuring data consistency and accuracy through rigorous validation processes.

With extensive experience in the field, we have developed a proprietary GenAI-based technology that is uniquely tailored to our organization. This advanced technology enables us to scan a wide array of relevant information sources across the internet. Our data-gathering process includes:

Searching through academic conferences, published research, citations, and social media platforms
Collecting and compiling diverse data to build a comprehensive and detailed database
Continuously updating our database with new information to ensure its relevance and accuracy

2. Primary Research

To complement and validate our secondary data, we engage in primary research through local tie-ups and partnerships. This process involves:

Collaborating with local healthcare providers, hospitals, and clinics to gather real-time data.
Conducting surveys, interviews, and field studies to collect fresh data directly from the source.
Continuously refreshing our database to ensure that the information remains current and reliable.
Validating secondary data through cross-referencing with primary data to ensure accuracy and relevance.

Combining Secondary and Primary Research

By integrating both secondary and primary research methodologies, we ensure that our database is comprehensive, accurate, and up-to-date. The combined process involves:

Merging historical data from secondary research with real-time data from primary research.
Conducting thorough data validation and cleansing to remove inconsistencies and errors.
Organizing data into a structured format that is easily accessible and usable for various applications.
Continuously monitoring and updating the database to reflect the latest developments and trends in the healthcare field.

Through this meticulous process, we create a final database tailored to each region and domain within the healthcare industry. This approach ensures that our clients receive reliable and relevant data, empowering them to make informed decisions and drive innovation in their respective fields.