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

South Korea Artificial Intelligence (AI) in Diagnostics Market Analysis

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South Korea Artificial Intelligence (AI) in the diagnostics market is projected to grow from $0.01 Bn in 2022 to $0.17 Bn by 2030, registering a CAGR of 36% during the forecast period of 2022-30. The market will be driven by collaborations among businesses, academia, and healthcare providers and a rise in demand for precise diagnostics. The market is segmented by component & by diagnosis. Some of the major players include Lunit, IBM Watson Health & Siemens Healthineers.

ID: IN10KRDH002 CATEGORY: Digital Health GEOGRAPHY: South Korea AUTHOR: Vidhi Upadhyay

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South Korea Artificial Intelligence (AI) in Diagnostics Market Executive Summary

South Korea Artificial Intelligence (AI) in the diagnostics market is projected to grow from $0.01 Bn in 2022 to $0.17 Bn by 2030, registering a CAGR of 36% during the forecast period of 2022-30. Korea's healthcare system is divided into two parts: compulsory social health insurance and medical aid. All people are covered by the National Health Insurance (NHI) system. Contributions from insured people and government subsidies are the two main sources of NHI funding. South Koreans spent around $3.9 thousand per capita on health in 2021 (The OECD defines health spending as the cost of healthcare goods and services). According to WHO statistics from 2020, the number of coronary heart disease fatalities in South Korea was 28,043 (or 11.19% of total deaths).

In South Korea, the AI in diagnostics situation is fast expanding, with the rising application of AI technology across numerous medical disciplines. The government's support for AI development, together with the country's outstanding technical infrastructure, lays a solid basis for the field's future expansion. AI is being used to analyze medical pictures including X-rays, CT scans, and MRIs in order to detect problems and deliver more accurate diagnoses. AI is being utilized to aid in the diagnosis of diseases like cancer and heart disease. Moreover, it is also used to evaluate tissue samples, such as those obtained from biopsies, in order to detect anomalies and offer more precise diagnoses; and to analyze genetic data in order to detect mutations and forecast the likelihood of acquiring specific illnesses. AI may also be used to create individualized treatment regimens for patients based on their genetic profiles.

south korea artificial intelligence in diagnostics market

Market Dynamics

Market Growth Drivers

South Korea possesses one of the greatest internet connections in the world, with around 97.57 percent of its people utilizing the internet. Also, South Korea was one of the countries with the fastest average mobile internet connection speed in the world. Some South Korean businesses are exploring AI-based diagnostics solutions. Lunit, a South Korean business, has built an AI platform for evaluating medical images to help in the identification of lung and breast cancer. Moreover, The Korean government is aggressively investing in artificial intelligence technologies. They unveiled an AI plan that will place them among the top five AI contenders by 2023. The rising population has led to rising requirements for diagnostic technologies which is also another factor aiding the growth of the market.

Market Restraints

The integration of numerous data sources, such as medical records and imaging data, is essential for AI in diagnostics. Even so, there may be problems in the interchange between different healthcare platforms and data sources in South Korea, which might hinder the usefulness of AI in diagnoses. Moreover, Lack of clarity regarding regulations, limitations to data availability, technical challenges which could make the adoption difficult for the practitioners, and privacy concerns are major impediments to the expansion of the market in South Korea.

Competitive Landscape

Key Players

Lunit (KOR)
IBM Watson Health
Siemens Healthineers
Philips Healthcare
GE Healthcare
Google Health
AliveCor, Inc.
Riverain Technologies
VUNO (KOR)
Eone Diagnomics Genome Center (KOR)

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
March 2022, GE Healthcare and a Top Korean Hospital intend to utilize GE's New Edison Digital Health Platform to Boost the AI Ecosystem

Healthcare Policies and Regulatory Landscape & Reimbursement Scenario

The South Korean government has aggressively promoted the development of artificial intelligence in healthcare and has created a regulatory framework to regulate the usage of AI-based solutions. The Ministry of Food and Drug Safety (MFDS) is in charge of regulating medical devices, including those that use AI technology, and has produced criteria for AI-based medical device clearance.

The National Health Insurance Service (NHIS) is South Korea's principal insurer of healthcare services, providing compensation for medical devices and services. The NHIS has devised a reimbursement strategy for AI-based medical devices that covers items that have been authorized by the MFDS and have shown clinical efficacy.

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.