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AI/ML Medical Device Market: Factors, Opportunities, & Future Outlook

Written by BIS Research | Sep 5, 2024 5:34:24 AM

The integration of artificial intelligence (AI)/machine learning (ML) is one of the key trends being witnessed in the healthcare industry. AI has a wide range of applications in healthcare, such as faster and more accurate detection of diseases, generation of patient-specific treatment plans, predictive analysis, and risk assessment. 

According to BISResearch, the global artificial intelligence/machine learning medical device market was valued at $4,011.7 million in 2022 and is anticipated to reach $35,458.2 million by 2032, witnessing a CAGR of 24.35% during the forecast period 2022-2032.

AI-enabled medical devices consist of both hardware/systems as well as software solutions classified as a medical device (SaMD). To date, the vast majority of AI-enabled medical devices have been approved as clinical decision support tools for radiological applications, with indications such as:

  • Detection of suspicious lesions
  • Enabling better imaging of various parts of the body
  • Contouring and segmentation of images
  • Reconstruction of images

 

Companies in the global artificial intelligence/machine learning medical device market are expected to continue investment in the research and development of AI-enabled medical devices across a wide range of clinical applications other than radiology as well. Moreover, while AI-enabled SaMDs are much more prevalent currently, technological advancements are expected to drive the growth of the system/ hardware segment during the forecast period 2022-2032.

Key Factors Impacting the Global Artificial Intelligence/Machine Learning Medical Device Market

The global artificial intelligence/machine learning medical device market is anticipated to be influenced by various factors during the forecast period 2022-2032. The key factors driving growth include the presence of a large ecosystem of companies offering AI solutions, growing demand in the field of radiology and cardiology, growing demand for wearable sensors, and large number of government initiatives. The factors restraining market growth include the lack of transparency and accountability and the challenges related to the identification and minimization of bias.

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Key Technologies in Artificial Intelligence Medical Device Market

  • Diagnostic Imaging: AI-powered imaging systems can analyze medical images, such as X-rays, MRIs, and CT scans, with high accuracy. These systems can detect anomalies, identify diseases, and assist radiologists in making precise diagnoses.
  • Predictive Analytics: AI and ML models can predict disease onset, progression, and patient outcomes by analyzing historical data and identifying risk factors. Predictive analytics tools help in early intervention and proactive healthcare management.
  • Robotic Surgery: Robotic surgical systems equipped with AI and ML enhance the precision and control of surgical procedures. These systems can assist surgeons in performing complex surgeries with minimal invasiveness, reducing recovery times and improving patient outcomes.\
  • Patient Monitoring: AI-driven patient monitoring devices continuously track vital signs and health parameters, alerting healthcare providers to potential issues in real-time. These devices enable remote monitoring, reducing the need for frequent hospital visits.

 

Artificial Intelligence/Machine Learning Medical Device Market by Region

North America has a technologically advanced digital healthcare landscape. Furthermore, the presence of several established companies and startups, as well as the adoption of several AI initiatives, have resulted in this region holding the maximum share in the global artificial intelligence/machine learning medical device market in 2022, followed by Europe. The less stringent regulatory system and government initiatives are factors leading to the rise of AI-enabled medical devices approved and commercialized in the region. Moreover, regions such as Asia-Pacific, and Rest-of-the-World are anticipated to register significant growth during the forecast period 2022-2032 owing to factors such as government initiatives to support the advancement of AI integration in healthcare and the expansion of market players into these geographies.

Future Outlook

The AI/ML medical device market is expected to grow rapidly, driven by ongoing technological advancements and increasing adoption in healthcare. Key trends to watch include:

  1. Expansion of Telemedicine and Remote Monitoring: The COVID-19 pandemic has accelerated the adoption of telemedicine and remote patient monitoring. AI/ML-powered devices will continue to play a crucial role in providing real-time, remote healthcare solutions.

  2. Enhanced Drug Discovery and Development: AI and ML are being increasingly used in drug discovery and development, speeding up the process and reducing costs. These technologies can identify potential drug candidates, predict drug efficacy, and optimize clinical trials.

  3. Collaborative Research and Development: Partnerships between AI/ML companies, healthcare providers, and academic institutions will foster innovation and accelerate the development of cutting-edge medical devices.

  4. Focus on Preventive Care: AI and ML will shift the focus from reactive to preventive healthcare, enabling early detection and intervention. This proactive approach will reduce the burden of chronic diseases and improve population health outcomes.

 

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Conclusion

The global artificial intelligence/machine learning medical device market is a fragmented market having a large number of established players and digital health startups developing AI-enabled medical devices for a wide range of applications. Trends such as government support through investments and AI initiatives and investor funding are expected to continue during the forecast period 2022-2032 and drive the growth of the market. Moreover, while AI is more commonly being integrated into software solutions currently, technological advancements are expected to lead to overcoming challenges associated with embedding AI in hardware systems.