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How to Use Machine Learning in Healthcare

Healthcare is one of the biggest industries in the world. The average life expectancy has increased dramatically in the past century, and that’s in no small part due to the technological advancements that enable it.

While the technology has substantially advanced since the olden days, new solutions such as AI and Machine Learning promise to provide healthcare with a second renaissance. Even the most minute and minor details of every process can be streamlined to near perfection, using computing, of course. While present in healthcare, ML still has a lot of potential for future implementation in healthcare. 

Is Machine Learning Being Used in Healthcare Today? 

Yes, machine learning plays a massive role in healthcare already, and the future seems very bright for this combination. As of now, machine learning is used for everything from predicting possible illnesses to recommending potential treatments. 

Machine learning has practically endless capabilities in assisting medical professionals with everything, from paperwork to the development of new medical procedures and solutions. 

Some of the most notable things machine learning is already bringing to the healthcare table are:

  • Smart patient records
  • Streamlined diagnostics
  • Drug and procedure development
  • Disease prediction 
  • Smart imaging 

Healthcare professionals can use machine learning to select ways to improve their industry, streamline a lot of processes, and ultimately save human lives. Aside from direct involvement in the medical sector, machine learning also plays a crucial preventive role.

Through machine learning, monitoring becomes that much better, allowing specialists to determine potential issues that aren’t yet apparent but have the potential to impact our lives. Some of these are up-and-coming diseases and pandemics, general pollution, and many other factors that might affect our overall health. 

Primary Use Cases of Machine Learning in Healthcare

Smart Patient Records

One of the things that healthcare relies on heavily is patient records. Improving and streamlining patient records can help medical professionals predict possible issues that may arise, solve existing problems, and assess particular situations. 

Patient records contain all the information on a patient’s past diagnoses, health condition, and insight into their physical and mental health. Smart patient records become a possibility through machine learning, and they’re widely used across the medical world. 

Smart patient records simplify and streamline patient records, make them better in almost every way, and more useful to the medical professionals.

Streamlined Diagnostics

Diagnostics used to take quite a lot of time, testing, and trial – and it still does to an extent. Through the advancement of machine learning, diagnosis becomes a far simpler ordeal than it used to be. Diagnoses can now be predicted before they occur, allowing the patient to prevent nasty issues from arising and giving the medical professional information which they can use to help the patient.

Machine learning helps doctors simplify and streamline diagnosing, which can be life-saving at best. At worst, it could streamline the diagnosis process, making it faster, better, and more accurate.

Drug and Procedure Development

We’re amid the COV-SARS-2 pandemic, which is currently ravaging the world, ruining lives and livelihoods alike, and posing a significant threat to the global populace’s health. Vaccines have been around for a while now, but their development has always been slow. Now, through machine learning, that process can be streamlined, simplified, and, most importantly, sped up. Right now, top-of-the-line companies such as Pfizer are using machine learning to aid them in the development of a covid drug that has the potential to save millions of lives. 

Aside from drugs, machine learning is also useful in helping medical professionals develop new procedures that help patients with existing diseases and disorders. 

Disease Prediction 

Disease prediction is the first step to disease prevention, and machine learning enables both. Through advanced artificial intelligence and machine learning, healthcare facilities worldwide can predict issues that haven’t yet affected the patient.

This early prediction allows doctors to prescribe treatments that eliminate the issue before it arises or drastically cut down its severity. That is especially useful in treating cancer, where early detection is vital. 

Smart Imaging 

Smart imaging is one of the most exciting new technologies in healthcare, enabled solely through machine learning. Through smart scans and imaging, artificial intelligence can connect the images and scans directly to the patient’s file. That allows for further analysis, better predictions, and a fantastic boost to clinical effectiveness. 

The Probable Future of ML in Healthcare 

It’s tough to speculate on what role machine learning can fulfill in the healthcare world, but if we had to take a guess, it would probably be streamlining all its current operations. Machine learning is already being used to improve healthcare, and as the technology behind machine learning progresses, so will its application in the healthcare world.

Artificial intelligence is already being used to save lives daily through prevention methods, prediction, and optimization of existing solutions to age-old problems.

What’s stopping machine learning from seeing more implementation in healthcare isn’t that machine learning isn’t sophisticated enough – it’s that machine learning and AI isn’t exactly sufficient for full implementation in the healthcare industry.

If an AI makes a mistake in any other sector, it’s unlikely that this mistake will result in human life loss, but it’s a very present and grave danger in healthcare. 

Final Thoughts 

Artificial intelligence and machine learning are a duo that will undoubtedly change the world as we know it. We’ve seen the industrial and digital revolutions come and pass, but the AI revolution has the potential to change the world to a much greater extent. 

While both of these technologies are buzzwords at this point, they’re not yet sophisticated enough to be fully implemented into our day-to-day lives. However, it doesn’t mean that the future won’t provide fantastic feats of technology to streamline everyday activities, simplify how we handle technology, and improve our quality of life by a considerable margin.

AI and ML aren’t only reliant on each other, as data is a massive player in both of these technologies, and the world of data science is continually on the rise as well. AI and ML have massive industrial applications at this point, and they’re finding their way into more than just these three industries with each and passing day. 

What will the future hold for machine learning in industrial applications? No one can tell, but what we can tell is that the future looks bright for machine learning. 

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