Artificial Intelligence in Healthcare Market is Projected to Reach USD 187.57 billion by 2030 at a CAGR of 16.7% | SNS Insider

Artificial Intelligence in Healthcare Market was valued at USD 14.09 billion in 2022. It is projected to reach USD 187.57 billion by 2030, exhibiting a remarkable compound annual growth rate (CAGR) of 38.2% during the forecast period from 2023 to 2030.

Artificial Intelligence (AI) has emerged as a transformative force within the healthcare industry, revolutionizing the way medical professionals diagnose, treat, and manage diseases. With its ability to analyze vast amounts of data and identify patterns, AI has the potential to enhance patient outcomes, streamline operations, and reduce costs.

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The exponential growth of the AI in Healthcare market is driven by several factors. Firstly, the increasing adoption of electronic health records (EHRs) and the digitization of healthcare data have created a wealth of information that can be leveraged by AI algorithms. These algorithms can quickly process and interpret this data, providing valuable insights to healthcare providers.

Moreover, the rising demand for personalized medicine and precision healthcare has further fueled the integration of AI in healthcare systems. AI-powered tools can analyze genetic data, patient history, and other relevant factors to develop tailored treatment plans, improving patient outcomes and reducing adverse events.

Major Players Listed in the Report are as Follows:
Enlitic, Inc., General Vision, Inc., IBM Corporation, Google Inc., Intel Corporation, Microsoft Corporation, Next IT Corporation, iCarbonX, Welltok, Inc., Nvidia Corporation and other players.

Artificial Intelligence in Healthcare Market Segmentation as Follows:

By Offering type
Hardware
Software
Services

By Technology
Machine Learning
Natural Language Processing
Context-aware Computing
Computer Vision

By Application
Patient Data & Risk Analysis
Inpatient Care & Hospital Management
Medical Imaging & Diagnostics
Lifestyle Management & Monitoring
Virtual Assistants
Drug Discovery
Research
Healthcare Assistant Robots
Precision Medicine
Emergency Room & Surgery
Wearables
Mental Health
Cybersecurity

By End User
Hospital & Healthcare Providers
Patients
Pharmaceuticals & Biotechnology Companies
Healthcare Payers

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Additionally, the COVID-19 pandemic has accelerated the adoption of AI in healthcare. From early detection and diagnosis to drug discovery and vaccine development, AI has played a crucial role in combating the global health crisis. As a result, governments and healthcare organizations worldwide are investing heavily in AI technologies to strengthen their healthcare infrastructure and enhance pandemic preparedness.

However, despite the immense potential of AI in healthcare, there are challenges that need to be addressed. Concerns regarding data privacy, security, and ethical considerations surrounding AI algorithms must be carefully navigated to ensure patient trust and regulatory compliance.

In conclusion, the Artificial Intelligence in Healthcare market is poised for substantial growth in the coming years. The convergence of advanced technologies, increasing healthcare digitization, and the need for improved patient outcomes are driving the adoption of AI in healthcare and paving the way for a revolution in the industry.

Table of Content
Chapter 1 Introduction
Chapter 2 Research Methodology
Chapter 3 Artificial Intelligence in Healthcare Market Dynamics
Chapter 4 Impact Analysis (COVID-19, Ukraine- Russia war, Ongoing Recession on Major Economies)
Chapter 5 Value Chain Analysis
Chapter 6 Porter's 5 forces model
Chapter 7 PEST Analysis
Chapter 8 Artificial Intelligence in Healthcare Market Segmentation, By Offering type
Chapter 9 Artificial Intelligence in Healthcare Market Segmentation, By Technology
Chapter 10 Artificial Intelligence in Healthcare Market Segmentation, By Application
Chapter 11 Artificial Intelligence in Healthcare Market Segmentation, By End User
Chapter 12 Regional Analysis
Chapter 13 Company profile
Chapter 14 Competitive Landscape
Chapter 15 Use Case and Best Practices
Chapter 16 Conclusion

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This release was published on openPR.