Germany Artificial Intelligence (AI) in Diagnostics Market Report 2022 to 2030

Germany Artificial Intelligence (AI) in Diagnostics Market Analysis

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Germany's Artificial Intelligence (AI) in the Diagnostics market is projected to grow from $0.04 Bn in 2022 to $0.36 Bn by 2030, registering a CAGR of 33.2% during the forecast period of 2022 - 2030. The market will be driven by supportive and collaborative initiatives of the government and the technical breakthroughs in the field of AI and machine learning. The market is segmented by component & by diagnosis. Some of the major players include Siemens Healthineers, Ibex & Innoplexus.

ID: IN10DEDH002 CATEGORY: Digital Health GEOGRAPHY: Germany AUTHOR: Vidhi Upadhyay

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Germany Artificial Intelligence (AI) In Diagnostics Market Executive Summary

The Germany Artificial Intelligence (AI) in the diagnostics market is projected to grow from $0.04 Bn in 2022 to $0.36 Bn by 2030, registering a CAGR of 33.2% during the forecast period of 2022 - 2030. Germany is the world's third-biggest medical technology industry, behind the United States and Japan, and is also the largest European business, double that of the French market and three times the value of that of Italy, the United Kingdom, and Spain. In Germany, health insurance is required, and coverage is almost universal. The statutory health insurance (SHI) system is made up of 110 sickness funds (as third-party payers) that cover around 88% of the population. According to WHO data published in 2020, the number of Coronary heart disease fatalities in Germany reached 147,055, accounting for 20.98% of all fatalities.

In Germany, Artificial Intelligence (AI) in the diagnostics market is quickly expanding, with an emphasis on offering novel solutions to the healthcare industry. Factors such as the growing burden of chronic illnesses, the increased need for enhanced diagnostic accuracy and efficiency, and technical breakthroughs in the field of AI and machine learning fuelled the market. Medical imaging is a prominent area of AI use in diagnostics in Germany, with AI algorithms used to interpret pictures from X-rays, CT scans, and MRI scans. This technique allowed radiologists to increase their diagnostic precision and efficiency, resulting in quicker and more precise medical diagnoses, such as cancer and heart disease. Another use of AI in diagnostics was the creation of diagnostic tools for infectious diseases.

In May 2022, Germany and India agreed to collaborate on Artificial Intelligence (AI) businesses, as well as AI research and applications in sustainability and healthcare.

germany artificial intelligence in diagnostics market analysis

Market Dynamics

Market Growth Drivers

In October 2019, The German Research Fund (DFG) created a new AI imaging prioritized initiative called "Radiomics: Next Generation Medical Imaging," with the goal of autonomously evaluating medical imaging data and thereby obtaining new image information for diagnoses. AI and radionics in radiology can already assess changes in tissue structures considerably quicker, and even uncover what the naked eye might have missed. Moreover, in order to stimulate innovation in the field of AI diagnostics, the German government is promoting collaboration among many stakeholders, including academic institutes, entrepreneurs, and established enterprises. Other factors such as the rising burden of chronic illnesses, increased need for enhanced diagnostic accuracy and efficiency, and technical breakthroughs in the field of AI and machine learning are also driving the market.

Market Restraints

AI systems can be challenging and need a significant amount of technical knowledge to build, implement, and operate. This means that healthcare companies may need to invest significantly in technological infrastructure, software, and employees in order to implement these systems. These systems may also require considerable testing and validation, which may be time-consuming and costly. Moreover, other challenges such as data privacy and security concerns, technical challenges, regulatory compliance, limited data availability, and resistance to change can also limit the growth of the market.

Competitive Landscape

Key Players

Siemens Healthineers
GE Healthcare
IBM Watson Health
Philips Healthcare
Google Health
Ibex
Innoplexus (DEU)
RetinAI (DEU)

Notable Deals

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 November 2022, Google Health reached an agreement with iCAD to commercialize mammography AI
July 2021, Ibex Medical Analytics (Israel), an innovator in AI-powered medical diagnostics, and Sana Kliniken Berlin-Brandenburg, Germany's 3rd largest private hospital group, declared the first deployment and clinical evaluation in Germany of an AI-based platform that assists pathologists during a routine cancer diagnosis

Healthcare Policies and Regulatory Landscape & Reimbursement Scenario

German and EU directives, standards, and safety requirements oversee the German medical device market. After a one-year delay, the EU Medical Device Regulation (MDR), which included stricter screening, approval, and compliance requirements, went into full force on May 26, 2021. The Federal Ministry of Health is in charge of developing and implementing healthcare policies and regulations. The ministry has been actively involved in the formulation of policies concerning the use of artificial intelligence in healthcare, particularly diagnostics. ELNET Germany established the German Israeli Health Forum for Artificial Intelligence (GIHF-AI) in 2021. The forum's focus is on the digitization of the healthcare sector, with an emphasis on the use of artificial intelligence (AI) and machine learning (ML).

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

Artificial Intelligence (AI) in Diagnostics Market Segmentation

By Component Outlook Type (Revenue, USD Billion):
- Software
- Hardware
- Services

By Diagnosis Outlook Type (Revenue, USD Billion):
- Cardiology
- Oncology
- Pathology
- Radiology
- Chest and Lung
- Neurology
- Others

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.