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Medical Devices in 2025: An AI Impact Analysis
Medical Devices in 2025: An AI Impact Analysis
Transforming Medical Imaging, Patient Monitoring, Ophthalmic and Cancer Diagnostics through Implementation of AI
RELEASE DATE
31-Mar-2020
31-Mar-2020
REGION
North America
North America
Research Code: D957-01-00-00-00
SKU: HC03280-NA-TR_24282
$4,950.00
In stock
SKU
HC03280-NA-TR_24282
Description
Medical device manufacturers are increasingly incorporating artificial intelligence (AI) in their systems with the aim to better assist healthcare providers and also improve care provided to the patients. AI systems have the ability to acquire data, deploy logical rules for processing the data, generate reasonable solutions and automatically recognize and rectify mistakes. These abilities have enabled the systems to make comprehensive analysis of the patient’s condition from large set of medical data, reduce clinical variations, decrease physicians’ burnout in turn improving decision making at the point of care. This research service (RS) highlights the innovations in platforms that are using AI in areas such as medical imaging, patient health monitoring, cancer and ophthalmic diagnostics.It also discusses the impact of these innovations, funding, drivers and challenges, and future growth opportunities.
RESEARCH: INFOGRAPHIC
This infographic presents a brief overview of the research, and highlights the key topics discussed in it.Click image to view it in full size
Table of Contents
1.1 Scope of the Research
1.2 Research Methodology
1.3 Research Methodology (continued)
2.1 Enhanced Utility of AI Systems Driving Adoption Across the Medical Device Industry
2.2 Broad Spectrum use of AI across Different Healthcare Application Areas
2.3 Innovations in AI-based Medical Devices Contributing to Growing Number of Patents in this Space
2.4 Imaging & Diagnostics Account for the Bulk of AI Patents Across Medical Devices Domain
3.1 Technology Segmentation Based on Application
3.1.1 Enhancing Screening of Eye Diseases Through AI
3.1.2 AI-based Systems for Detection of Diabetes-associated Retinal Diseases
3.1.3 AI-based Systems for Glaucoma Diagnosis
3.1.4 AI-based Systems for Diagnosis of Different Eye Diseases
3.2 Technology Segmentation Based on Application
3.2.1 Enabling Effective Cancer Diagnosis Through AI-based Platforms
3.2.2 AI-based Systems for Breast Cancer Diagnosis
3.2.3 AI-based Systems for Cancer Diagnosis Through Biological Samples
3.2.4 AI-based Systems for Skin Cancer Diagnosis
3.2.5 Combining AI with Endoscopes for Enhanced Cancer Diagnosis
3.3 Technology Segmentation Based on Application
3.3.1 Improving Patient Health Outcomes Through AI-assisted Patient Monitoring
3.3.2 Wearables for Monitoring Vital Health Parameters
3.3.3 Remote Patient Monitoring System for Respiratory Conditions
3.3.4 AI-driven Platforms for Bedside Patient Monitoring
3.4 Technology Segmentation Based on Application
3.4.1 Emergence of AI-based Medical Imaging as an Indispensable Radiology Tool
3.4.2 Diagnosis of Neurological Diseases Through Medical Imaging Data
3.4.3 AI-based Visualization Systems for Cancer Diagnosis
3.4.4 AI-powered Applications for Chest Imaging
3.4.5 AI-based Medical Imaging Platforms for Detecting Cardiovascular Diseases
4.1 Impact of Technology Accelerators and Challenges
4.1.1 Enhanced Accuracy and Early Disease Detection Ability to Spur Market Adoption
4.1.2 Inadequate Curative Data Set and Cyber Security Issues to Impede Systems Use
5.1 Assessment of Government Funding for AI-driven Systems
5.2 Analysis of NIH Funding for AI-driven Systems
5.3 National Institute of Aging Leads the Funding for AI-based Medical Devices Technology Research
5.4 AI-based Medical Imaging Platforms Receive Maximum Funding Compared to Cancer Diagnostics, and Other Application Areas
5.5 Growth Opportunities: Convergence of AI and AR/VR
5.6 Growth Opportunities: Convergence of AI and Electroceuticals
5.7 Growth Opportunities: Convergence of AI and Medical Robotics
6.1 AI to Usher in Enhanced Quality of Clinical Care
6.2 Benchmarking Rubrics
6.3 Impact of AI to be Relatively High for Medical Imaging Analysisas compared to other Application Areas
6.4 Breaking the Iron Triangle in Healthcare Through AI
6.5 Go-to-Market Strategy for Driving AI Adoption in Key Countries
6.6 Future Application Areas for AI in Disease Detection and Management
7.1 AI Enabling Effective Diagnosis of Coronavirus Disease (COVID-19)
7.2 Tracking Disease Spread and Facilitating Effective Treatment Development Through AI
8.1 Key Industry Contacts
8.1 Key Industry Contacts (continued)
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Popular Topics
Medical device manufacturers are increasingly incorporating artificial intelligence (AI) in their systems with the aim to better assist healthcare providers and also improve care provided to the patients. AI systems have the ability to acquire data, deploy logical rules for processing the data, generate reasonable solutions and automatically recognize and rectify mistakes. These abilities have enabled the systems to make comprehensive analysis of the patient’s condition from large set of medical data, reduce clinical variations, decrease physicians’ burnout in turn improving decision making at the point of care. This research service (RS) highlights the innovations in platforms that are using AI in areas such as medical imaging, patient health monitoring, cancer and ophthalmic diagnostics.It also discusses the impact of these innovations, funding, drivers and challenges, and future growth opportunities.
| No Index | No |
|---|---|
| Podcast | No |
| Author | Neeraj Nitin Jadhav |
| Industries | Healthcare |
| WIP Number | D957-01-00-00-00 |
| Is Prebook | No |