With RPM, vital signs and other health data are passively collected from the patient and sent to the cloud where AI models can alert appropriate healthcare professionals if the person starts to become unwell. This ability to manage throughput--to separate the signal from the noise--is the power of AI. It lets healthcare professionals focus on the patients who need their attention the most, and it helps those who don't need healthcare attention feel safer and more secure at home. Many patients simply require the reassurance that everything is OK and is going to be OK.
The healthcare industry is currently suffering from a host of issues. Knowledge sharing between hospitals, determination of patient adherence to medications, and the efficient management of surgical procedures are just three topics in a long list of areas that need improvement. All of these issues have the same thing in common: the healthcare industry has a data problem.
The Internet of Healthcare Things is coming -- and for all intents and purposes, it's already here. According to a new report by Aruba Networks, by next year, 87 percent of healthcare organizations will have adopted IoT. Moreover, more than three-quarters of these organizations believe the technology will completely transform the healthcare industry. As IoT is injected into everything from X-ray machines to patient monitors and hospital meters, networking demands will change and providers will need to revamp cybersecurity to address an increasingly connected threat landscape. But alongside these infrastructure needs will come several benefits and an increased return on investment for care organizations that choose to embrace a connected future.
Building off my last post, I want to use the same healthcare data to demonstrate the use of R packages. Packages in R are stored in libraries and often are pre-installed, but reaching the next level of skill requires being able to know when to use new packages and what they contain. With that let's get to our example. When working with vectors and strings, especially in cleaning up data, gsub makes cleaning data much simpler. In my healthcare data, I wanted to convert dollar values to integers (ie.
This meet up is anyone in the community interested in learning about opportunities in the healthcare industry and its need for innovation, design, technology and startups. This will be a monthly meet up to bring together healthcare leaders, executives, technologists, designers, professionals, care organizations, insurance companies, funders, software and device vendors and other interested parties for brain stimulating discussions and coffee. Come join us and make an impact to the healthcare industry and society as a whole.