Australia Artificial Intelligence (AI) in Diagnostics Market Analysis Report [2022-30]

Australia Artificial Intelligence (AI) in Diagnostics Market Analysis

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The Australia Artificial Intelligence (AI) in the diagnostics market is projected to grow from $0.01 Bn in 2022 to $0.14 Bn by 2030, registering a CAGR 36.5% during the forecast period of 2022 - 2030. 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 Siemens Healthineers, Philips Healthcare & Harrison.

ID: IN10AUDH002 CATEGORY: Digital Health GEOGRAPHY: Australia AUTHOR: Vidhi Upadhyay

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Australia Artificial Intelligence (AI) In Diagnostics Market Executive Summary

The Australia Artificial Intelligence (AI) In the diagnostics market is projected to grow from $0.01 Bn in 2022 to $0.14 Bn by 2030, registering a CAGR of 36.5% during the forecast period of 2022 - 2030. Australia's healthcare system is among the greatest in the world, with all Australians receiving safe and affordable treatment. It is cooperatively managed by the federal, state and territory, and municipal governments of Australia. Overall health expenditures in 2022-23 were anticipated to be $105.8 billion, accounting for 16.8% of total Australian Government spending. An estimated 151,000 new cases of cancer were projected to be diagnosed in Australia in 2021, representing an average of 413 cases each day. Breast cancer is expected to be the most often diagnosed cancer in 2021, followed by prostate cancer.

AI would enable healthcare practitioners in interpreting massive amounts of data, such as medical images, test findings, and patient history, in order to make more informed and accurate diagnoses. It may be used to identify cancer, triage crucial discoveries in medical imaging, flag acute abnormalities, assist radiologists in prioritizing life-threatening patients, diagnose cardiac arrhythmias, forecast stroke outcomes, and aid in chronic disease management. In Australia, numerous private firms are developing AI-powered diagnostic tools for a variety of illnesses such as skin cancer, lung cancer, and heart disease. SkinVision, for example, is a smartphone app that utilizes artificial intelligence to scan photographs of skin lesions and offer a risk rating for melanoma. The Therapeutic Goods Administration (TGA) cleared this gadget for usage in Australia.

Australia Artificial Intelligence (AI) in diagnostics market analysis

Market Dynamics

Market Growth Drivers

The scarcity of healthcare professionals is more strongly in rural and remote areas of the country, where one in every four Australians lives. These places struggle to attract and retain healthcare workers and rely more heavily on nurses than metropolitan areas due to a smaller concentration of healthcare experts. Artificial intelligence (AI) can assist alleviate this shortfall by increasing efficiency and decreasing the pressure on healthcare personnel, allowing them to focus on more difficult duties. Moreover, The Australian e-Health Research Centre (AEHRC), a partnership between CSIRO and the Queensland Government, has been working on an AI-powered application to aid with breast cancer screening such an increase in collaboration among business, academia, and healthcare providers, with an emphasis on creating and testing new AI-powered diagnostic tools along with other factors such as rise in demand for precise diagnostics, technological advancements, government initiatives and rising incidence of chronic illnesses are expected to drive the market in the future.

Market Restraints

Concerns about data privacy and security, legal barriers, restricted access to health data, a lack of validation and review, and cost are all challenges that might impede the development and implementation of AI-powered diagnostic tools. Achieving regulatory compliance may be a difficult task, and extensive validation and review are required to verify the safety, effectiveness, and accuracy of these instruments. Moreover, the cost of development and implementation might be prohibitively expensive, restricting their use in resource-constrained contexts.

Competitive Landscape

Key Players

IBM Watson Health
Siemens Healthineers
Philips Healthcare
GE Healthcare
Google Health
AliveCor, Inc.
Riverain Technologies
Aidoc Medical Ltd. (ISR)
Harrison (AUS)
See-Mode Technologies (AUS)
Maxwell Plus (AUS)

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
December 2022, Riverian and Thynk Health Join Together to Combat Lung Cancer Using Powerful AI and Deep Learning Technology
November 2022, During RSNA 2022, Philips promotes AI-powered diagnostic technologies and transformational workflow solutions
In November 2022, Google Health reached an agreement with iCAD to commercialize mammography AI

Healthcare Policies and Regulatory Landscape

In December 2021, the Australian Alliance for Artificial Intelligence in Healthcare (AAAiH) announced the release of its Australia Roadmap for Artificial Intelligence in Healthcare. The roadmap includes 24 proposals divided into eight key categories that address essential concerns such as safety, quality, ethics, industry development, and customer requirements.

Medical devices that integrate or are software, including software as a medical device or software that relies on certain hardware to work, are known as software-based medical devices and are regulated in Australia by the Therapeutic Goods Administration (TGA).

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.