AI has made some key contributions to healthcare providers around the world. The hype to leverage machine-based learning in the landscape has recently emerged. There are some particular forms of computer intelligence to consider when thinking about its role in healthcare. Most of the computer generated solutions now emerging in healthcare do not depend on single computer intelligence. Rather, they use human created algorithms as a basis for analyzing data.
Machine learning relies on neural networks which involves multilevel probabilistic analysis, allowing computers to stimulate and even expand in a way that the human mind processes data. Another AI variant, deep learning, which learns to recognize patterns in distinct layers, has become increasingly useful in healthcare. Each neural network layer operates both independently and in agreement―separating aspects like size, color, and shape. Such new visual tools are transforming diagnostic medicine. AI has improved the diagnosis of patients’ healthcare by mining health data to identify possible risks, predicting patient at risk. The technology also supports surgical procedures using robotics.
Prescription analytics is one of the machine learning methodologies used to relate both descriptive and predictive analytics and to determine the best outcome among various known parameters. This can process new data automatically to improve the accuracy of predictions and offer the best decision options. Progress in the speed of computing and mathematical algorithms led to the emergence of prescriptive analytics.
UUID (Universally Unique Identifier) scans wristband, prescription, and intravenous barcodes, which can all be shared among the connected systems. This UUID makes it easy to associate with EHR, nurse call, and patient data monitoring call at the same time. At present, many hospitals leverage technologies like nurse scanners for patient wristband barcodes.
Currently, several applications of AI are being implemented in hospitals. It is mandatory to improve the accuracy of delivering quality care by integrating patient monitoring devices and EHRs. Healthcare industry should begin to invest more in prescriptive analytics to improve its overall care delivery, efficiency, and to better understand patients.