The medical devices industry continues to be a hotbed of innovation, with activity driven by increased need for homecare, preventative treatments, early diagnosis, reducing patient recovery times and improving outcomes, as well as a growing importance in technologies such as machine learning, augmented reality, 5G and digitalisation. In the last three years alone, there have been over 450,000 patents filed and granted in the medical devices industry, according to GlobalData’s report on Artificial Intelligence in Medical Devices: AI-assisted radiology.
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.
150+ innovations will shape the medical devices industry
According to GlobalData’s Technology Foresights, which plots the S-curve for the medical devices industry using innovation intensity models built on over 550,000 patents, there are 150+ innovation areas that will shape the future of the industry.
Within the emerging innovation stage, AI-assisted radiology, motion artefact analysis, and treatment evaluation models are disruptive technologies that are in the early stages of application and should be tracked closely. MRI image smoothing, AI-assisted EHR/EMR, and AI-assisted CT imaging are some of the accelerating innovation areas, where adoption has been steadily increasing. Among maturing innovation areas are computer-assisted surgeries and 3D endoscopy, which are now well established in the industry.
Innovation S-curve for artificial intelligence in the medical devices industry
AI-assisted radiology is a key innovation area in artificial intelligence
Artificial Intelligence (AI) assisted radiology has the potential to enhance the utility of traditional radiology from manually diagnosing changes in organ features as an indication of a disease to a true diagnostic tool that relates features to specific diseases in an automated and accurate process. This will greatly help the radiologist and other clinicians in interpreting images and provide more accurate and timely diagnoses which will improve patient outcomes.
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 40+ companies, spanning technology vendors, established medical devices companies, and up-and-coming start-ups engaged in the development and application of AI-assisted radiology.
Key players in AI-assisted radiology – a disruptive innovation in the medical devices 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 radiology
Source: GlobalData Patent Analytics
Siemens is one of the leading patent filers in AI-assisted radiology. Some other key patent filers in the medical devices space include Canon, General Electric, SVXR, Samsung Group and GE Healthcare.
In terms of geographic spread, IBEX Innovations leads the pack, followed by Elekta, Asto CT and Varex Imaging. By means of application diversity, Varex Imaging leads, with ConforMIS and Nikon in second and third place, respectively.
AI has the potential to augment radiology workflows in radiology in many ways. AI-assisted radiology can improve surgical and exam planning, image reconstruction, image analysis, and support clinical decision making. AI-assisted radiology is expected to become a new set of novel tools in the hands of the radiologist. Such use of AI is likely to be ubiquitous and somewhat invisible to the physician, blending into the background of clinical decision-making processes.
To further understand the key themes and technologies disrupting the medical devices industry, access GlobalData’s latest thematic research report on Medical Devices.