Generative Artificial Intelligence (AI) in the Medical Devices Sector – Thematic Intelligence

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Access and explore in-depth trends and insights in our Generative Artificial Intelligence (AI) in the Medical Devices Sector’ report:

  • An overview of generative AI theme in the medical devices sector.
  • An assessment of the current use of generative AI in medical devices.
  • Access comprehensive details on use cases, risks, and limitations of AI in the medical devices market.
  • Highlights the leading companies and disruptors in the generative AI theme.

How is the ‘Generative Artificial Intelligence (AI) in the Medical Devices Sector’ report different from other reports in the market?

  • GlobalData’s thematic research ecosystem is a single, integrated global research platform that provides an easy-to-use framework for tracking all themes across all companies in all sectors. It has a proven track record of identifying important themes early, enabling companies to make the right investments ahead of the competition and secure that all-important competitive advantage.
  • Develop and design your corporate strategies through an in-house expert analysis of artificial intelligence by understanding the primary ways in which this theme is impacting the healthcare industry.
  • Stay up to date on the industry’s major players and where they sit in the value chain.
  • Identify emerging industry trends to gain a competitive advantage.

 We recommend this valuable source of information to anyone involved in:

  • Medical Devices Manufacturers/Technology Leaders and Startups
  • Business Development and Market Intelligence
  • Investment Analysts and Portfolio Managers
  • Professional Services – Investment Banks, PE/VC firms
  • M&A/Investment, Management Consultants, and Consulting Firms

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Generative Artificial Intelligence (AI) in Medical Devices Thematic Overview

Of the five advanced AI technologies receiving the most attention today, generative AI is the fastest growing and is likely to pose a threat to every business across every sector in the coming years. The impact will expand across sectors and business functions as generative AI becomes more accurate and is able to provide reliable factual advice. Use cases include diagnostic imaging, personalized health, reducing healthcare spending, and more.

The Generative Artificial Intelligence (AI) in Medical Devices thematic intelligence report provides an overview of this emerging technology and its wider impacts on medical devices, while also providing insights on the immediate and future effects of Generative AI.

Report Pages 53
Regions Covered Global
Value Chain ·       Hardware

·       Data Management

·       Foundation AI

·       Advanced AI Capabilities

·       Delivery

Use Cases ·       Research and Development

·       Prevention

·       Diagnostics

·       Treatment

·       Monitoring

Leading Vendors ·       DiagnaMed

·       Google Cloud Platform

·       Clarify Health

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Full AI - Value Chain Analysis

The AI value chain consists of hardware, data management, foundation AI, advanced AI capabilities, and delivery.  Generative AI (or creation) falls within the advanced AI capabilities category. Other subsegments under the advanced AI capabilities value chain are human-AI interaction, decision-making, motion, and sentience.

AI Value Chain Analysis

AI Value Chain Analysis

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Generative AI in Medical Devices – Risks and Limitations

The risks posed by generative AI in medical devices theme are data access,  racial and ethnic inequalities, environmental limitations, data processing, ethical risks, data privacy, self-diagnosing, and financial. The collection and use of patient healthcare data and information through AI medical products could conflict with regulations around the globe. Hence, medical device companies as well as healthcare professionals should remain vigilant and understand when such regulations apply.

Generative AI in Medical Devices Risks and Limitations Analysis

Generative AI in Medical Devices Risks and Limitations Analysis

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Generative AI in Medical Devices – Medical Industry

Generative AI can improve personalized healthcare by collecting data from patients via wearable devices. These wearables can provide continuous, real-time data that can complement traditional data sources such as imaging, patient records, and more. Generative AI tools can help healthcare professionals make more accurate diagnoses by finding abnormalities that a healthcare professional may have missed. It can also enhance existing imaging techniques by generating high-quality images of organs using data from low-resolution images (such as ultrasounds).

Some of the use cases of generative AI employed in the medical devices industry are research and development, prevention, diagnostics, treatment, and monitoring. For example, DiagnaMed plans to roll out its AI brain health platform, CERVAI, in Q4 2023. CERVAI provides a two-pronged analysis of brain health and has a Brain Age Estimation tool that uses an electroencephalogram headset and machine learning model to predict brain age. The software can be used to reveal whether an individual’s brain is aging faster than their actual age.

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Leading Vendors

Some of the leading vendors making their mark within the AI in medical devices theme are:

  • DiagnaMed
  • Google Cloud Platform
  • Clarify Health

DiagnaMed:  It is a Canadian generative AI healthcare solutions company, based out of Toronto, Ontario. They are working on a number of AI products, including CERVAI, a proprietary brain health AI platform, and Health GenAI, a suite of generative AI solutions powered by OpenAI’s ChatGPT platform for the healthcare market.

To know more about the leading vendors in the generative AI in medical devices theme, download a free report sample

Segments Covered in the Report

AI Value Chain Outlook

  • Hardware
  • Data Management
  • Foundation AI
  • Advanced AI Capabilities
  • Delivery
DiagnaMed
Google Cloud
Clarify Health Solutions
Segmed
NVIDIA
Charmhealth
Philips
AWS
eClinicalWorks
care.ai
Transcarent
Olympus

Table of Contents

Executive Summary

Generative AI overview

Use cases

Risks and limitations

Competitive landscape

Scorecards

Our thematic research methodology

Contact us

Frequently asked questions

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