US Artificial Intelligence in Healthcare Market Report 2022 to 2030

US Artificial Intelligence (AI) in Healthcare Market Analysis

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US Artificial Intelligence (AI) in the healthcare market is projected to grow from $2.9 Bn in 2022 to $51.3 Bn by 2030, registering a CAGR of 43.22% during the forecast period of 2022-30. The US Artificial Intelligence (AI) in the Healthcare market is a rapidly growing industry that involves the use of AI technologies to improve patient care, reduce costs, and increase efficiency in healthcare delivery. IBM Watson Health offers a range of AI-powered healthcare solutions, including clinical decision support, medical image analysis, and patient monitoring.

ID: IN10USDH003 CATEGORY: Digital Health GEOGRAPHY: US AUTHOR: Shivam Zalke

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US Artificial Intelligence (AI) in Healthcare Market Executive Summary

US Artificial Intelligence (AI) in the healthcare market is projected to grow from $2.9 Bn in 2022 to $51.3 Bn by 2030, registering a CAGR of 43.22% during the forecast period of 2022-30.

Some of the key factors propelling the market's expansion are the expanding datasets of digital patient health information, the rising desire for individualized treatment, and the rising demand for lowering healthcare costs. The increase in demand for early illness diagnosis and better understanding has been attributed to the expanding global geriatric population, changing lifestyles, and increased incidence of chronic diseases. Healthcare systems are increasingly adopting and integrating artificial intelligence (AI) and machine learning (ML) algorithms to precisely forecast illnesses in their early stages based on past health records.

Moreover, early patient diagnosis of underlying health issues is made possible by deep learning technology, predictive analytics, content analytics, and Natural Language Processing (NLP) tools. The Covid-19 outbreak increased demand for AI technology and made these sophisticated technologies' potential more apparent. Healthcare systems extensively embraced these technologies for the quick diagnosis and detection of various virus strains and made use of tailored data to enhance outbreak management. In order to quickly and reliably identify patients who tested positive for Covid-19, AI/ML algorithms were used in the diagnostic field. These technologically advanced modules were trained using datasets of chest CT scans, symptoms, pathological findings, and exposure history.

US artificial intelligence in healthcare market analysis

Market Dynamics

The following are some of the aspects that influence the application of AI in healthcare:

Personalized medicine is in greater demand, and AI technology can assist in determining the best courses of action for different patients based on their particular genetic and clinical profiles.
Rising medical expenses AI in healthcare may save costs by increasing efficiency and minimizing mistakes.
Development of technology Advanced AI algorithms and machine learning approaches are making it possible to analyze medical data in a way that is more accurate and exact.
Expansion of healthcare data availability A plethora of data is being made available by the growing digitalization of healthcare data, which may be utilized to create and hone AI algorithms.

Competitive Landscape

Key Players

The US AI in the healthcare market is characterized by a large number of players, ranging from startups to established healthcare companies. Some of the key players in the market include:

IBM Watson Health
GE Healthcare
Google Health
Amazon Web Services (AWS)
Microsoft Healthcare

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

US 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.