For centuries, patrons have sought out fortune tellers with a doe-eyed mysticism that they have the answers they’ve been searching for. Sure, Data Analytics and AI don’t have a foggy crystal globe or ornate gypsy headdress, but it’s quite possible experts are onto something close to that…
The untapped potential of Artificial Intelligence in medical imaging may be one of the single most promising areas of development in the healthcare realm. Theoretically, it would allow experts to produce imaging for things like, “image acquisition, processing to aided reporting, follow-up planning, data storage, data mining” and more (TMR). Basically, it would take the human error out of medicine. Arguably one of the most precise and thorough offerings to date, it continues to excel in the classification and characterization of improved tissue-based detection and characterization. Constructed much like a neural network architecture of interconnected nodes, “each node of the network performs a weighted sum of the input data that are consequently transferred to an activation function.” All this cryptic science talk basically means that AI would help doctors make educated decisions based on the data they’ve accumulated over the course of their career. With this dream on its way to a reality, it makes complete sense what AI in the medical field has the potential to be unstoppable.
Often, the healthcare field is criticized for its mass, indiscriminate evaluation, and execution of medical care. Advancements in areas such as AI Medical Imaging, could turn the industry on its head through its ability to support individualized treatment on a patient-by-patient basis, as well as expedited diagnoses. It could even provide, “quantitative evaluations of radiographic characteristics” in fields such as radiation oncology where AI has been, “applied to several distinct image modalities that are used at various stages of the treatment” (TMR). Basically, it’s potential applications are a big deal.
It would be foolish to dismiss the role COVID-19 played in these advancements. Due to its intuitive extraction capabilities, AI has been a technological “favorite” due to its extraction feature. It’s often been used to, “identify and differentiate bacterial and viral pneumonia on pediatric chest radiographs” as well as identify, “various imaging features of chest CT, resulting in increased popularity for AI in medical imaging market amid the pandemic” (TMR).
As COVID-19 cases begin to make a resurgence, it’s likely that hospitals will begin to invest more resources into AI for its inherent scalability and remote access functionality.
For those that prefer more traditional means of playing “doctor,” it’s likely that the idea of robot-like technology taking over will not be met with open arms. In fact, medical practitioners are likely apprehensive for fear that the technology is both unreliable as well as offensive to those that invested countless years in pursuit of their specialty. It is also possible that a full-scale implementation of this technology may be perceived with a lack of cost-effectiveness, practicality and safety by providers (TMR). And these obstacles only began to present themselves as catalyst to the mere thought that AI may begin to stake out a larger role within the field.
Impactful change is often met with great opposition. Despite the political, ethical, and theoretically repercussions of a larger AI and AI Medical Imaging presence, it is quite possible that these sorts of technological integrations are an inevitability.
Sure, perhaps AI-supported Medical Imaging couldn’t have predicted by a fortune teller or medium, but maybe the magic in data is that we don’t have to see it to foresee its impact.
The Systech Solutions, Inc. Blog Series is designed to showcase ongoing innovations in the data and analytics space. If you have any suggestions for an upcoming article, or would like to volunteer to be interviewed, please contact Olivia Klayman at email@example.com.
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