Switzerland Artificial Intelligence in Diagnostics Market Report 2022 to 2030

Switzerland Artificial Intelligence (AI) in Diagnostics Market Analysis

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Switzerland's Artificial Intelligence (AI) in the diagnostics market is projected to grow from $xx Bn in 2022 to $xx Bn by 2030, registering a CAGR of xx% during the forecast period of 2022-30. The market will be driven by the country's strong emphasis on innovation research and development and its already existing robust healthcare infrastructure. The market is segmented by component & by diagnosis. Some of the major players include IBM Watson Health, Siemens Healthineers & Altoida.

ID: IN10CHDH002 CATEGORY: Digital Health GEOGRAPHY: Switzerland AUTHOR: Vidhi Upadhyay

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Switzerland Artificial Intelligence (AI) in Diagnostics Market Executive Summary

Switzerland's Artificial Intelligence (AI) in the diagnostics market is projected to grow from $xx Bn in 2022 to $xx Bn by 2030, registering a CAGR of xx% during the forecast period of 2022-30. Healthcare in Switzerland is universal and is controlled by the Swiss Federal Law on Health Insurance. There are no free state-provided health services, however, private health insurance is necessary for all citizens residing in Switzerland. According to the OECD, Swiss healthcare spending will reach 11.9% of GDP in 2020, with per capita spending on healthcare greater than in any other European country. In 2020, the major causes of mortality in Switzerland were noncommunicable diseases such as cardiovascular disease (26.9%) and cancer (22.2%).

Switzerland has been a pioneer in the application of Artificial Intelligence (AI) in diagnostics. The government places a high value on innovation, and the healthcare industry has been fast to embrace new digital technology. Radiology is an important field of use for AI in diagnosis. The Swiss healthcare system has started analyzing medical imaging such as X-rays, CT scans, and MRI scans using AI-based software. AI algorithms can interpret pictures quickly and more correctly than human radiologists, enabling more accurate and timely diagnoses.

In November 2021, Ibex Medical Analytics, the innovator in AI-powered cancer diagnostics, and Kantonsspital Baselland, a healthcare provider in Northwestern Switzerland, announced the first Swiss installation of an AI system to assist pathologists with a routine cancer diagnosis. Moreover, in March 2022, Katalysen Ventures formed an alliance as a venture developer with Swiss digital medtech firm Med4Cast to promote the use of ai in medical diagnostics.

Market Dynamics

Market Growth Drivers

The government has a national policy for healthcare digitization, which includes an emphasis on AI applications. Moreover, the Swiss Innovation Agency (Innosuisse) has funded research initiatives that investigate the application of AI in diagnostics. The country's strong emphasis on innovation and research and development is a fundamental driver of the rise of AI in diagnostics in Switzerland. The Swiss Federal Institute of Technology (ETH) and the University of Zurich are two institutions that are actively studying AI applications in diagnostics. The modern healthcare infrastructure in Switzerland is another driver of the expansion of AI in diagnostics. Switzerland's private healthcare industry is technologically competent and substantially invests in new technologies. This has helped to stimulate innovation in the AI diagnostic sector by creating an ecosystem in which AI businesses may thrive.

Market Restraints

One of the most significant issues is the lack of regulatory certainty. In Switzerland, there is presently no complete legislative framework for artificial intelligence in healthcare, and there are doubts regarding the ethical and legal consequences of utilizing AI in diagnosis. Concerns about data privacy are another issue. The collection and processing of medical data are very sensitive, and rigorous data protection procedures are required to preserve patient privacy and security.

Competitive Landscape

Key Players

GE Healthcare
IBM Watson Health
Siemens Healthineers
Philips Healthcare
Google Health
AliveCor, Inc.
Ibex Medical Analytics
Altoida (CHE)
Scailyte (CHE)
b-rayZ (CHE)

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
November 2022, During RSNA 2022, Philips promotes AI-powered diagnostic technologies and transformational workflow solutions

Healthcare Policies and Regulatory Landscape and Reimbursement Scenario

The Federal Office of Public Health (FOPH) in Switzerland is in charge of monitoring the use of medical equipment, particularly AI-based diagnostic tools. The FOPH reviews medical devices based on their safety, performance, and efficacy, and if they fulfill the standards, they are assigned a "Swissmedic" registration number.

In terms of reimbursement, the Swiss healthcare system is based on a mandated health insurance system, with all citizens having to have basic health insurance. The Federal Office of Insurance (FOI) is in charge of establishing whether medical treatments and procedures, including diagnostic tests, are cost-effective and should be covered by mandated health insurance.

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.