Digitization has become a new norm in most industries, including healthcare. Data analysis and interpretation are commanding most niches. Machine learning (ML) and Artificial Intelligence (AI) are critical in handling the most complex data challenges. The healthcare industry struggles to meet the increasing medical demands of consumers and strives for efficiency in record keeping, data analysis, and processes. Machine learning provides better services to consumers through more personalized care and detecting and treating diseases quickly.

Machine Learning is a form of AI (Artificial Intelligence), including representing and evaluating data then finally optimizing it. Machine Learning comes in various types, including unsupervised, supervised, reinforcement, and semi supervised.

While it may come as a surprise to come, Machine learning has several benefits regarding healthcare. Here are just a few examples of how Machine Learning has made the medical world better.


Regarding health informatics, machine learning helps to smooth the recordkeeping process. The health sector has struggled for a long time in maintaining good records. It is one of the significant challenges the industry faces. The use of EHRs, electronic health records have been essential in curbing the problem. As a result, patients are provided with better healthcare services that are cost-effective.

Predictive Analytics

Predictive analytics is integral in improving healthcare. Together with health informatics, patients receive positive results through improved processes. Machine Learning provides a platform for predictive analysis helping medical practitioners in detecting diseases accurately and developing the proper treatment.

Data Integrity

Data integrity is critical in medical practitioners’ decision-making. Inaccurate data creates gaps in predictive analytics, which in return can affect a patients’ diagnosis or treatment. Machine Learning requires a high level of data integrity to ensure that patients get the proper treatment.

Personalized Medicine

Health practitioners have demanding jobs that they hardly get enough time to analyze complex data. Machine Learning plays a vital role in ensuring that medical practitioners provide patients with precision medicine despite their busy schedules. As a result, they provide personalized medical services, meeting the needs of consumers.

Robotic Surgery

Technology is becoming inevitable in the health sector. Robot-assisted surgeries are gaining traction by the day. They assist medical practitioners in performing complex procedures more accurately. With precision as a priority, robotic surgery is proving to be more accurate compared to conventional methods. Some areas where robot-assisted surgeries come in handy include unclogging blood vessels and aiding in spine surgery.