For years, the healthcare industry has been changing shape and direction meteorically. Machine learning is spearheading the Healthcare space, once seen as an industry that technology would struggle to pierce into. Not only has ML become a popular part of the industry, but it is going to play a major role in it’s future development and change the way that healthcare is administered, analyzed and delivered for decades to come.
So, who are the best machine learning companies in healthcare right now?
As part of the overall Google/Alphabet program, it’s no surprise that Deepmind is ranking high up on the ML companies impressing in healthcare. Deepmind is all about managing medical records faster and easier for more reliable health services. It can process huge sums of data in a matter of minutes. It’s already found a place at the Moorfields Eye NHS Hospital in the UK as it’s used to try and make sure eye treatments become more and more accurate over time.
Zephyr has really hit the market in a big way in the last few years, with the aim of making therapeutic choices for patients more accurate than ever before. By giving diverse and intelligent data to medical staff, their aim is to help reduce the amount of time that it takes therapies and treatments to be recommended and then put into action. By ensuring that data can be analyzed faster and treatment accuracy improved, Zephyr could play a vital role in the long-term future of healthcare.
Another very impressive part of the healthcare ML industry, this is a cloud-based system that offers analysis for all patients. It’s basically a way of looking at how good the care was for a patient, and the likelihood that said care could see them either have to return to the hospital in the future or not. That’s going to help make sure that, by improving scores and reducing return likelihoods, businesses can make it much easier for people to get the help, care and assistance that they need.
This is a growing platform that is coming directly from the Silicon Valley, all about ensuring that patient outcomes can line up with the financial costs. Using evidence-fed algorithms and machine learning helps ensure that insights can be provided to ensure a more individualized method of care can be delivered to each and every patient. By reducing the burden on doctors, this offers access to information and details that simply would not be possible otherwise.
WatsonPaths, a rather interesting branch of IBM, is becoming impressive in the world of data analysis. The aim is to give medical experts a chance to build more consistent insights in terms of their electronic medical records for their staff. With these innovations, the hope is that, in time, physicians will be able to much easier and more accurately understand the needs and desires of patients to make a genuine difference in how they’re analyzed.