The healthcare industry continues to be a hotbed of innovation, with activity driven by telemedicine, real-time diagnostics, smart hospitals and access to digital therapies, as well as the growing importance of technologies such as artificial intelligence (AI), the Internet of Things (IoT), augmented reality (AR), robotics and data management practices. In the last three years alone, there have been over 106,000 patents filed and granted in the healthcare industry, according to GlobalData’s report on Artificial Intelligence in Healthcare: AI-assisted MRI.
However, not all innovations are equal and nor do they follow a constant upward trend. Instead, their evolution takes the form of an S-shaped curve that reflects their typical lifecycle from early emergence to accelerating adoption, before finally stabilising and reaching maturity.
Identifying where a particular innovation is on this journey, especially those that are in the emerging and accelerating stages, is essential for understanding their current level of adoption and the likely future trajectory and impact they will have.
200+ innovations will shape the healthcare industry
According to GlobalData’s Technology Foresights, which plots the S-curve for the healthcare industry using innovation intensity models built on over 443,000 patents, there are 200+ innovation areas that will shape the future of the industry.
Within the emerging innovation stage, drug delivery device security, microscopic image analysis models, and cellular imaging techniques are disruptive technologies that are in the early stages of application and should be tracked closely. Smart balloon catheters, automated immunoassay analysers, and AI-assisted MRI are some of the accelerating innovation areas, where adoption has been steadily increasing. Among maturing innovation areas are smart fitness training system and non-invasive physiological monitoring, which are now well established in the industry.
Innovation S-curve for artificial intelligence in the healthcare industry
AI-assisted MRI is a key innovation area in artificial intelligence
AI is widely used in magnetic resonance imaging (MRI) due to its MRI-specific soft tissue contrast, wide range of structural and physiological acquisition protocols, and its diagnostic potential.
GlobalData’s analysis also uncovers the companies at the forefront of each innovation area and assesses the potential reach and impact of their patenting activity across different applications and geographies. According to GlobalData, there are 50+ companies, spanning technology vendors, established healthcare companies, and up-and-coming start-ups engaged in the development and application of AI-assisted MRI.
Key players in AI-assisted MRI – a disruptive innovation in the healthcare industry
‘Application diversity’ measures the number of different applications identified for each relevant patent and broadly splits companies into either ‘niche’ or ‘diversified’ innovators.
‘Geographic reach’ refers to the number of different countries each relevant patent is registered in and reflects the breadth of geographic application intended, ranging from ‘global’ to ‘local’.
Patent volumes related to AI-assisted MRI
|Company||Total patents (2010 - 2021)||Premium intelligence on the world's largest companies|
|Siemens||263||Unlock company profile|
|Heartflow||251||Unlock company profile|
|Koninklijke Philips||170||Unlock company profile|
|Canon||87||Unlock company profile|
|Toshiba||83||Unlock company profile|
|Samsung Group||79||Unlock company profile|
|Hitachi||73||Unlock company profile|
|General Electric||68||Unlock company profile|
|Bayer||64||Unlock company profile|
|Toshiba Medical Systems||35||Unlock company profile|
|Arterys||33||Unlock company profile|
|Shanghai United Imaging Healthcare||32||Unlock company profile|
|Elekta||29||Unlock company profile|
|Heuron||24||Unlock company profile|
|Hyperfine Research||24||Unlock company profile|
|BrainLAB||24||Unlock company profile|
|Synaptive Medical||23||Unlock company profile|
|Hyperfine||21||Unlock company profile|
|Assistance Publique - Hopitaux de Paris||19||Unlock company profile|
|Centre National de la Recherche Scientifique||17||Unlock company profile|
|Shimadzu||16||Unlock company profile|
|Neurophet||14||Unlock company profile|
|Johnson & Johnson||11||Unlock company profile|
|International Business Machines||9||Unlock company profile|
|Ricoh||9||Unlock company profile|
|Massachusetts General Hospital||9||Unlock company profile|
|Medrad||9||Unlock company profile|
|Omniscient Neurotechnology||8||Unlock company profile|
|Cedars-Sinai Health System||8||Unlock company profile|
|General Hospital||8||Unlock company profile|
|Dragerwerk||8||Unlock company profile|
|Tel Hashomer Medical Research Infrastructure and Services||8||Unlock company profile|
|United States Of America||8||Unlock company profile|
|SimBioSys||7||Unlock company profile|
|Fujifilm Holdings||7||Unlock company profile|
|Genetic Innovations||7||Unlock company profile|
|Children's Medical Center||7||Unlock company profile|
|Bracco Injeneering||7||Unlock company profile|
|Darmiyan||7||Unlock company profile|
|Oki Electric Industry||6||Unlock company profile|
|Teijin||6||Unlock company profile|
|Antaros Medical||6||Unlock company profile|
|BioProtonics||6||Unlock company profile|
|NovoCure||5||Unlock company profile|
|Beijing SenseTime Technology Development||5||Unlock company profile|
|Esaote||5||Unlock company profile|
|Exxellence||5||Unlock company profile|
|PT Soho Global Health||5||Unlock company profile|
|Acuitas Medical||5||Unlock company profile|
|Shenzhen United Imaging Healthcare||5||Unlock company profile|
Source: GlobalData Patent Analytics
Siemens is the leading patent filer in the AI-assisted MRI market. Some other leading patent filers include Heartflow and Koninklijke Philips.
In terms of application diversity, BrainLAB leads the pack, followed by Teijin and Heartflow. With regards to geographic reach, Bracco Injeneering leads, followed by Hyperfine Research and Shenzhen United Imaging Healthcare.
AI will turn MRI into a new era of quantitative imaging that will use massive data structures, replacing its most qualitative therapeutic applications. Clinical diagnostic criteria can be met by AI-based algorithms that are currently being developed. The algorithms have outstanding quality and efficiency.
To further understand how artificial intelligence is disrupting the healthcare industry, access GlobalData’s latest thematic research report on Artificial Intelligence (AI) in Healthcare.