Artificial intelligence (AI) which is the mimicking of human understanding by computers is finally a reality in medicine, more so in
This company was established in 2011 with an approximate $100 million funds. Its main focus has been to reinvent the ultrasound machine big time by reducing it into a single silicone chip that could comfortably sit in your smartphone. Even though it could disrupt the imaging equipment market, it could provide medical imaging to more than 60% of the world population that have no access to imaging services.
Zebra was established in 2014 with $20 million funds. So much to develop cloud based radiology services. In 2016 they announced that they had algorithms that automatically detected bone mineral density, breast cancer etc advancing the field of imaging equipment further. Basically, you can upload CT scans and get correct diagnosis within an hour as a result of the revolutionary algorithms.
Based in California, Arteys took an approximate $13.72 million funds to be founded in 2011. It is the first company to produce an imaging equipment platform that is FDA approved for use in clinical settings. It is a cloud based platform that provides imaging analytics in a matter of seconds, way faster than an average human.
Other companies include: Enlitic, Imagen, RADlogics, Bay Labs, Mindshare, Entopsis, Proscia
AI may be both a promise and pitfall for radiologists. However, considerations should be made on fair grounds.
More medical enterprises are image-enabled making physicians overloaded with more data than they can absorb, archive, or even recall. Health care providers’ effectiveness directly depends on how efficiently images can be managed. Therefore, if radiologists are overwhelmed, care givers suffer immensely. Here is where AI could step in and save the day by handling the rising number of images and data. AI has the ability to turn radiologists into super experts by being an effective, efficient imaging equipment tool. Algorithms used in AI can be trained to monitor and recognize disease patterns reducing time taken to come up with histories, diagnose, and treat patients.
Algorithms with the ability to translate as well as summarize EMRs help to understand unstructured observations that technicians who do referrals often include in records. By so doing, a patient’s condition can be well understood. Even more, referring physicians can use these algorithms as decision-aiding tools to narrow down the number of scans needed for a patient. As a result of efficiency, testing costs reduce while care giving improves.
However, with all the promise, AI may still turn the tide on radiologists. This is because the art of interpreting medical images solely lay with radiologists. As machines acquire interpretive skills, they threaten the position of technicians in the medical field. This can be overcome by collaboration, making both AI in imaging as well as radiologists a bigger part of care giving and management.
It will be interesting to watch what happens in the medical industry in the coming months and years with AI! Atlantis Worldwide is here to help with your refurbished radiology equipment needs. For more information on refurbished medical imaging equipment Contact Us!
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Meet the author: Vikki Harmonay