[ad_1]
While technological innovation, new business models and artificial intelligence (AI) have emerged in the forefront of the medical device industry in the last decade, medical imaging in particular benefited most from these trends.
A new analysis conducted by researchers at McKinsey & Company in New York, published on December 4 in Officer of the American College of Radiology identified four emerging technologies at the heart of global medical imaging startups: AI and machine learning, blockchain, real-time imaging (eg three-dimensional (3D) images, virtual reality) and incremental innovation technologies (eg 3D printing, portable imaging, telemedicine).
For their study, Alan Alexander, MD and colleagues analyzed the global launch scenario for new and emerging technologies in the acquisition, visualization, interpretation, storage and sharing of data in medical imaging. The researchers were left with a total of 146 startups who received more than $ 1.8 billion in investments in 446 separate transactions over the past five years. Of these startups, AI and blockchain were two of the most promising technologies found.
AI and machine learning
The AI and machine learning startups have the largest number of transactions and represent over 20% of the companies included in the analysis, according to the researchers. Technologies registered the highest number of startups (32) with over $ 500 million in transactions with investors, higher income, strong investor interest and high growth potential.
"E & # 39; [AI] has the potential to transform the way health care is delivered, with AI and machine learning solutions that complement doctors' work to enable the development of new therapeutic paradigms, "Alexander et al.
As the number of patients and complex cases continues to increase, the researchers explained that AI and machine learning could help radiologists increase the efficiency and accuracy of reading, prevent unnecessary tests and more easily integrate imaging data into electronic medical records.
Of the 32 startups, the researchers found that 22% of companies were focused on CT, 13% on each mammogram and magnetic resonance, nine percent on ultrasound, three percent on each nuclear image and X rays and 31% did not specified.
Furthermore, 72% of IA companies are developing deep learning technologies to identify injuries or anomalies; 12 percent includes the integration of electronic medical records for the self-population of measurements and comparisons; nine percent for workflow management to prioritize scans; and six percent for the use of reported results to improve decision-making.
