Netherlands Artificial Intelligence (AI) in Healthcare Market Analysis

Netherlands Artificial Intelligence (AI) in Healthcare Market Analysis


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Netherlands's Artificial Intelligence (AI) In healthcare market is projected to grow from $0.02 Bn in 2022 to $0.36 Bn by 2030, registering a CAGR of 45.72% during the forecast period of 2022 - 2030. The market will be driven by the country’s strong healthcare system, a culture of innovation and collaboration, and government assistance for research and development. The market is segmented by healthcare components & by healthcare applications. Some of the major players include Philips Healthcare, Aidence & Quantib.

ID: IN10NLDH003 CATEGORY: Digital Health GEOGRAPHY: Netherlands AUTHOR: Vidhi Upadhyay

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Netherlands Artificial Intelligence (AI) In Healthcare Market Executive Summary

Netherlands's Artificial Intelligence (AI) In healthcare market is projected to grow from $0.02 Bn in 2022 to $0.36 Bn by 2030, registering a CAGR of 45.72% during the forecast period of 2022-30. When it comes to healthcare, the Netherlands ranks among the top-performing countries in the world. The country's healthcare system is ranked second among 11 high-income countries by the Commonwealth Fund. The Dutch government is responsible for the Netherlands Healthcare System, which has been reviewed and improved several times since the mid-twentieth century. Neoplasms, circulatory system diseases, and mental and behavioural disorders were the leading causes of death.

Researchers at Nijmegen's Radboud University Medical Center created an AI algorithm that can analyse MRI scans of the brain and anticipate which individuals have a likelihood of developing Alzheimer's disease. In the Netherlands, artificial intelligence is being used in personalised medicine. To identify personalised treatment options, AI algorithms can analyse patient data such as genetic factors and medical history. The government has launched a programme called "ZorgTech" to encourage the development of new technologies, such as artificial intelligence (AI), to improve healthcare outcomes. The programme funds research and development projects that use artificial intelligence and other technologies to improve patient care. AI adoption and utilisation in healthcare are increasing in the Netherlands, with many good potential developments in the field. a number of obstacles to overcome, the Netherlands is well-positioned to remain a leader in the use of artificial intelligence in healthcare.

Netherlands Artificial Intelligence (AI) In Healthcare Market

Market Dynamics

Market Growth Drivers

The government established the "ZorgTech" programme to aid in the development of new technologies such as AI. In addition, the Dutch Data Protection Authority issued guidelines for the use of AI in healthcare, highlighting the significance of informed consent and data security.  Several other factors are driving the growth of artificial intelligence (AI) in healthcare in the Netherlands, including a strong healthcare system, a culture of innovation and collaboration, and government assistance for research and development. The country's emphasis on personalised medicine, as well as its use of electronic health records, provides a great deal of information for training AI algorithms and improving patient outcomes. Furthermore, the COVID-19 pandemic has hastened AI adoption in healthcare, with the technology being used to develop vaccines, predict outbreaks, and diagnose the disease.

Market Restraints

Concerns about data privacy and security, regulatory barriers, and the need for more knowledge and training for healthcare professionals to effectively use AI tools are all potential barriers to the growth of AI in healthcare in the Netherlands. Addressing these issues is critical to realising AI's full potential in healthcare in the Netherlands.

Competitive Landscape

Key Players

  • Philips Healthcare
  • IBM Watson Health
  • NVIDIA
  • Thirona (NLD)
  • Quantib (NLD)
  • Aidence (NLD)
  • Peptone (NLD)
  • LeQuest (NLD)
  • SkinVision (NLD)
  • MicroSure (NLD)

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

Artifical Intelligence (AI) in Healthcare Market Segmentation

The Artificial Intelligence (AI) in Healthcare Market is segmented as mentioned below:

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.

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Last updated on: 08 June 2023
Updated by: Anish Swaminathan

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