Healthcare Industry: Impact of Machine Learning
Machine learning (ML), and the application of artificial intelligence, are quickly gaining traction worldwide for their ability to deliver incredible value to the broad spectrum of industries in the world. However, this technology’s application in the healthcare sector has evinced special interest. Why? Well, because of the rapidly growing number of machine learning applications in healthcare and, of course, the countless benefits it offers to all the stakeholders involved in the process of delivering and receiving medical care.
ML can make extraordinary improvements to the healthcare system while reducing the subjectivity and fluctuation across the clinical findings. And, it is proactively showcasing promising outcomes while assisting clinicians to diagnose malignant growth, cancers, uncommon illnesses, and pathologies. ML-based systems could in truth outperform human beings in specific assignments.
Listed below are some of the key benefits machine learning offers for the world of healthcare:
1. Personalized treatment: It has been amply proven by research that personalized treatment is one of the most effective ways to manage the disease. To that end, machine learning helps by examining patient data including their symptoms, test reports, and medical history while empowering the doctors to put together treatment plans and medications that are personalized to the unique needs of the patient.
2. Early detection of diseases: Yet another compelling benefit hospitals and medical care providers stand to gain from the integration of machine learning is the ability to detect diseases in their early stages. A variety of supervised as well as unsupervised machine learning algorithms help make early detection of diseases a reality by analyzing historic and new data about a given disease and alerting doctors in case the symptoms qualify for the said disease. This allows doctors to quickly devise a treatment plan and ensure a better quality of life for their patients.
3. Robot-assisted surgery: Long gone are the days of archaic medical care and surgeries; we now live in a world where surgeons can be capably assisted by avant-garde technologies. In this context, machine learning-powered surgical systems and processes can be used to execute complicated surgical procedures albeit with reduced side effects, risk of pain, and blood loss among other things. Oh, and did we mention that machine learning-assisted surgeries also offer the benefit of quicker recovery after the surgery?
4. Prescription error analysis: Thousands of people suffer at the hands of incorrect prescriptions. Any mortality in this context is understandably unacceptable even though human errors or even system malfunction is bound to happen at some point or another. Thankfully, machine learning offers us a convenient and effective fix: this technology can be leveraged to examine historic EHR data and then compare said data against new prescriptions. In case a prescription breaks away from the typical pattern, it is immediately flagged to the appropriate personnel to ensure doctors can review said prescription and make adjustments in case that is deemed necessary. This further helps improve the quality of patient care as well.
There you have it ladies and gentlemen, some of the most compelling machine learning use cases in healthcare. As you can see, this novel technology stands to transform healthcare in some of the more advanced ways one could imagine. All the data collected by healthcare service providers, when processed with technologies such as machine learning, stands to help these providers and facilities achieve the most efficient and precise results while also delivering a significant boost to productivity and performance across the board. So, what are you waiting for? Go ahead and start looking for a trusted service provider to help you integrate machine learning into your healthcare business.
