How Hospitals Are Beginning to Leverage AI in Medical Diagnosis

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How Hospitals Are Beginning to Leverage AI in Medical Diagnosis

It goes without saying that technology and the healthcare field are inextricably linked. And artificial intelligence, in particular, otherwise known as machine learning, is starting to play a key role in medical diagnostics and treatment as well. Hospitals and healthcare facilities are already using AI in this fashion in many ways, and it’s certain that we’ll see increased use of machine learning in the future. 

Here are just a few examples of the way hospitals are leveraging AI to help patients:  

Predictive Medicine

Predictive medicine means using artificial intelligence to — you guessed it — make predictions about a patient’s health based on analysis of things like medical history, medications, procedure records, etc. Essentially, machine learning is able to take all of that information, synthesize and analyze it, and spit out predictions of what kind of health obstacles that patients might face in the future based on similar cases. Armed with that prediction, healthcare professionals can look for signs that confirm that diagnosis as time goes on and take steps to reverse any health problems as necessary.  

Comprehensive Diagnostics

Diagnostic work can also make use of AI technology in a similar way to that of predictive medicine. Every shred of health information about a given patient — medical history and records, genetics, family members’ health histories, medical imaging, etc. — can be fed to the computer, which analyzes it. From there, a diagnosis is reached based on all available data, and doctors and other healthcare professionals can base their treatment plans off of that recommendation. And since AI  

Robotic Surgery

You’re probably well aware that robotic surgery has been around for some time. This is one of the key areas where AI is used in the medical world. Robotic surgical arms can make much more precise maneuvers and incisions than the human hand, making surgeries that much safer. Plus, AI can learn how to improve its own procedures based on data from previous successful surgeries, resulting in more positive results from robotic surgery as time goes on.  

These are just a few of the many ways that hospitals and healthcare organizations are using AI to the advantage of patients. It remains to be seen how widespread this kind of technology becomes in the field, but all signs point toward a widespread adoption of these kinds of applications. 

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