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Artificial Intelligence in Healthcare Market Projected to Gain Significant Value through 2032

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Ganesh Shinde
Artificial Intelligence in Healthcare Market Projected to Gain Significant Value through 2032

In the end of 2021, the global artificial intelligence in healthcare market was estimated to be worth roughly US$ 7.0 billion. The market is expected to grow at a 38.5% CAGR and reach a value of US$ 181.8 billion by 2032.

In healthcare, artificial intelligence (AI) is used to interpret and analyse data in order to perform clinical diagnosis and provide appropriate treatment solutions for a problem. It analyses disease patterns and symptoms utilising a variety of technologies and powerful algorithms, while also providing improved direction, criticism, and assistance to healthcare providers. Furthermore, AI-powered systems can evaluate healthcare data via wearable smart devices, deliver digital and virtual consultations to patients, and provide drug formulation and management services.

North America is the largest market for AI in healthcare, followed by Europe and Asia-Pacific. The United States is the largest market in North America due to the high adoption rate of advanced technologies and the presence of key players in the region. Europe is also a significant market for AI in healthcare due to the increasing government initiatives to promote the use of AI in healthcare and the growing demand for personalized medicine.

Key Players:

  • Amazon Web Services Inc.
  • Cloudmedx Inc.
  • DeepMind
  • Enlitic Inc.
  • General Vision Inc.
  • Google Inc.
  • International Business Machines
  • iCarbonX
  • Intel Corporation
  • Medtronic
  • Micron Technology Inc.
  • Microsoft Corporation
  • Nuance Communications Inc.
  • Nvidia Corporation
  • Siemens Healthcare and Welltok Inc

Browse More@ https://www.futuremarketinsights.com/reports/artificial-intelligence-in-healthcare-market

Key Segments Covered in the Artificial Intelligence in Healthcare Industry Survey

By Offering:

  • Hardware
  • Software
  • Services

By Technology:

  • Machine Learning
  • Context-Aware Computing
  • Natural Language Processing
  • Deep Learning
  • Querying Method
  • Others

By Application:

  • Robot-Assisted Surgery
  • Virtual Nursing Assistant
  • Administrative Workflow Assistance
  • Fraud Detection
  • Dosage Error Reduction
  • Clinical Trial Participant Identifier
  • Preliminary Diagnosis
  • Others

By End User:

  • Healthcare Providers
  • Pharmaceutical and Biotechnology Companies
  • Patients
  • Others


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Ganesh Shinde
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