Hong Kong Artificial Intelligence (AI) in Diagnostics Market Analysis

Hong Kong Artificial Intelligence (AI) in Diagnostics Market Analysis


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Hong Kong's Artificial Intelligence (AI) in the diagnostics market is projected to grow from $1.6 Mn in 2022 to $18.75 Mn by 2030, registering a CAGR of 36% during the forecast period of 2022-2030. The market will be driven by the growing rate of chronic diseases and the government's strong support for the development and deployment of AI technology. The market is segmented by component & by diagnosis. Some of the major players include IBM Watson Health, Siemens Healthineers & Insilico.

ID: IN10HKDH002 CATEGORY: Digital Health GEOGRAPHY: Hong Kong AUTHOR: Vidhi Upadhyay

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Hong Kong Artificial Intelligence (AI) in Diagnostics Market Executive Summary

Hong Kong's Artificial Intelligence (AI) in the diagnostics market is projected to grow from $1.6 Mn in 2022 to $18.75 Mn by 2030, registering a CAGR of 36% during the forecast period of 2022-30. Hong Kong is the most efficient healthcare system in Asia, ranking 1st in the world. Hong Kong, like many other nations, offers both privatized and government healthcare. Every province and district of Hong Kong has a high concentration of clinics, hospitals, and Traditional Chinese Medicine (TCM) clinics, with 24-h emergency services and practitioners who are all globally qualified and experienced in their specialty. In 2021, coronary heart disorders were responsible for 37,158 hospital discharges and fatalities, accounting for 1.7% of all hospital discharges and fatalities.

AI-powered diagnostic systems can scan medical imaging and patient data to detect early warning signals of illnesses like cancer and heart disease. AI may be used to increase the accuracy of diagnosis by analyzing medical imaging such as CT scans, MRI scans, and X-rays. AI-powered imaging solutions can also assist radiologists in more promptly and precisely examining the Imaging. AI may be used to monitor patients with chronic conditions like diabetes and heart disease in order to detect early indicators of problems and act before they become severe. While AI in diagnostics is yet in its initial phases in Hong Kong, there is a considerable possibility for its use in improving healthcare outcomes and lowering costs.

In November 2022, A group of Hong Kong scientists from the Chinese University of Hong Kong (CUHK) created the world's first artificial intelligence (AI) model capable of detecting Alzheimer's disease by scanning a patient's retina pictures, possibly allowing more individuals to benefit from early diagnosis. In April 2022, A University of Hong Kong (HKU) engineering team created a new solution "REFERS" a new AI algorithm for high precision and economical medical imaging diagnostics.

Hong Kong artificial intelligence in diagnostics market analysis

Market Dynamics

Market Growth Drivers

The establishment of the Hong Kong Science and Technology Parks Corporation (HKSTP), a center for creative technology businesses, such as those working on the development of AI diagnostics, is one of the government's objectives. The HKSTP helps start-ups and entrepreneurs focusing on novel healthcare solutions, such as AI diagnostics, with funding, mentorship, and infrastructural assistance. The possibility for enhanced efficiency is one of the key drivers of AI in diagnostics. The Innovation and Technology Fund for Better Living gives financial support to enterprises developing healthcare solutions, while the Health and Medical Research Fund's Researcher Programme assists researchers in developing AI-based diagnosis and therapy solutions. The Hospital Authority has teamed with Tencent to build an AI-based diagnostic system for liver cancer, while the Hong Kong University of Science and Technology has partnered with Ping An Technology to develop an AI-based system for early diagnosis of diabetic retinopathy.

Market Restraints

AI algorithms require vast volumes of medical data to perform properly. Yet, in order to safeguard patient privacy, this data must be utilized with caution. Despite the potential benefits of AI in diagnostics, there could be a scarcity of medical data in Hong Kong for AI systems to train. This has the potential to restrict the precision and usefulness of Ai systems. AI algorithm research and deployment can be costly, limiting its access to minor medical facilities or those with limited resources. The use of AI in diagnostics presents several ethical considerations, including the possibility of algorithm bias and the role of medical experts in decision-making.

Competitive Landscape

Key Players

  • IBM Watson Health
  • Siemens Healthineers
  • Philips Healthcare
  • GE Healthcare
  • Google Health
  • AliveCor, Inc.
  • Riverain Technologies
  • Ping An Technology
  • iCarbonX
  • Niramai
  • Insilico (HKG)

Notable Deals

  1. 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
  2. November 2022, Google Health reached an agreement with iCAD to commercialize mammography AI
  3. In October 2022, Prudential plc and Google Cloud Establish Strategic Collaboration to Provide Access to Healthcare and Financial Security in Asia and Africa

Healthcare Policies and Regulatory Landscape

The Department of Health is in charge of ensuring the effectiveness and safety of medical devices and equipment, including those that employ artificial intelligence for diagnosis. They are also in charge of medical device registration and licensing. The Hong Kong Medical Council oversees medical practice in Hong Kong, which includes the use of artificial intelligence in medical diagnosis. They provide standards and restrictions for the application of AI technology in medicine.

Reimbursement Scenario

The Hong Kong government established the Voluntary Health Insurance Plan in April 2019 to encourage residents to obtain health insurance and to provide consumers with private healthcare services additional options. Tax deductions were also established by the government for taxpayers who acquired Certified Plans for themselves and/or designated families.

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.

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IBM Watson Health, Siemens Healthineers, Philips Healthcare, GE Healthcare, Google Health, AliveCor, Inc., Riverain Technologies, Ping An Technology, iCarbonX, Niramai & Insilico are the major players of Artificial Intelligence (AI) in the Diagnostics market in Hong Kong.

The growing rate of chronic diseases and the government's strong support for the development and deployment of AI technology are the two major drivers of Artificial Intelligence (AI) In the Diagnostics market in Hong Kong.

By 2030, it is anticipated that Artificial Intelligence (AI) in the diagnostics market will reach a value of $18.75 Mn from $1.6 Mn in 2022, growing at a CAGR of 36% during 2022-2030.


Last updated on: 31 May 2024
Updated by: Riya Doshi

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