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

US Artificial Intelligence (AI) in Diagnostics Market Analysis

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The US Artificial Intelligence (AI) in the diagnostics market is projected to grow from $0.42 Bn in 2022 to $4.11 Bn by 2030, registering a CAGR of 33% during the forecast period of 2022 - 2030. The market will be driven by the growing number of AI-based diagnostic companies and supportive government initiatives in the US. The market is segmented by component & by diagnosis. Some of the major players include IBM Watson Health, Siemens Healthineers & AliveCor, Inc.

ID: IN10USDH002 CATEGORY: Digital Health GEOGRAPHY: US AUTHOR: Vidhi Upadhyay

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US Artificial Intelligence (AI) in Diagnostics Market Executive Summary

The US Artificial Intelligence (AI) in the diagnostics market is projected to grow from $0.42 Bn in 2022 to $4.11 Bn by 2030, registering a CAGR of 33% during the forecast period of 2022 - 2030. In 2021, healthcare spending in the United States is projected to increase by 2.7% to $4.3 Tn, or $12,914 per person. Health spending accounted for 18.3% of the nation's Gross Domestic Product. The expected number of new cancer cases and fatalities in 2021 in the United States will have an estimated 1.9 million new cancer cases diagnosed and 608,570 cancer deaths. In 2020, over 697,000 individuals in the United States died from heart disease, accounting for one out of every five fatalities.

In the US, Artificial intelligence (AI) is rapidly gaining traction in the medical profession, which implies that many medical devices are beginning to include AI capabilities. Among these AI capabilities are improved imaging systems, smart robotics, wearable technologies, AI-based data processing, simulation platforms, and others. It is majorly utilized in radiology to help detect early indications of lung cancer on a chest X-ray. AI is being utilized in pathology to evaluate tissue samples in order to identify cancer and other chronic conditions. In cardiology identify patterns in the data that may indicate the risk of a heart attack or other cardiac event. Moreover, it is also being utilized to analyze patient data and uncover patterns and relationships that human specialists may not be able to see.

us artificial intelligence in diagnostics market analysis

Market Dynamics

Market Growth Drivers

The US government has allocated funds for AI development and research in healthcare. The National Institutes of Health (NIH) and the National Science Foundation (NSF), have both contributed funding for AI research in healthcare. boosting total growth and adoption. To promote the application of AI in healthcare, the US government has worked with industry leaders. The Department of Veterans Affairs (VA) has collaborated with industry giants like Google and IBM to create AI-powered diagnostic tools. The National Institutes of Health (NIH) has established the All of Us research initiative, which intends to collect health data from one million people to help AI research in healthcare. Apart from these government initiatives, the growing number of AI-based diagnostic companies in the healthcare industry, as well as increased investments by private investors in the development of newer and novel technologies that may give effective and rapid outcomes in diagnostic procedures, are driving market expansion.

In December 2022, Altris AI secured $1 million in a funding round headed by Runa Capital in order to grow its AI-enabled eye care diagnostics system. Altris AI, a US-based firm founded in Ukraine, developed solutions for the $58 billion worldwide ophthalmology sector.

Market Restraints

The application of artificial intelligence (AI) in diagnostics has the potential to transform healthcare in the United States. Yet, a number of obstacles are hindering its wider implementation. These difficulties include legislative ambiguity as the regulatory landscape for AI in healthcare In the US is still evolving which has created uncertainty for developers and investors, concerns about data quality and privacy, interoperability issues to integrate with existing healthcare systems with electronic health records, resistance to change by certain professionals and restricted access to technology due to high costs or lack of expertise.

Competitive Landscape

Key Players

IBM Watson Health
Siemens Healthineers
Philips Healthcare
GE Healthcare
Google Health
AliveCor, Inc. (USA)
Riverain Technologies (USA)
Aidoc Medical Ltd. (ISR)
Arterys (USA)
Paige.AI (USA)

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 & Reimbursement Scenario

The Food and Drug Administration (FDA) governs the use of medical equipment, including artificial intelligence diagnostic technologies. Before commercialization, the FDA has published advice for the development and use of AI-based medical devices, including diagnostic tools, and needs premarket evaluation and clearance or approval. The Federal Trade Commission (FTC) is in charge of ensuring that firms creating artificial intelligence diagnostic tools follow consumer protection laws and do not participate in misleading or unfair acts.

The Centers for Medicare and Medicaid Services (CMS) is in charge of determining medical service payment regulations in the United States, including those employing AI diagnostic technologies. AI diagnostics reimbursement varies based on the type of service performed, the payer, and the patient's insurance coverage.

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.