Cloud To Be Utilized By Microsoft And UCLA To Create Precision Medicine

 A partnership between Microsoft and the health department of the University of California, Los Angeles is now trying to determine of the future of medicine can be found in the healthcare data that are yet to be accessed. This might also be something that triggers companies such as Rend Tech Associates with their goal of providing cloud technology for the healthcare sector. Together, UCLA and Microsoft, is trying to create a platform so that it will be accessible to utilize artificial intelligence to gather data both in clinical results and research.

According to UCLA Health Sciences’ head of data officer, Dr. Mohammed Mahbouba, one of the things they are trying to accomplish with cloud technology is the possibility of discovering precision health.

Mahbouba believes that the next big thing for health care institutions after the overall use of electronics for accessing health records is machine learning. This is the inevitable path for the healthcare industry. With the use of the new platform, data will be gathered from a number of sources in order to be analysed in a holistic manner and gradually give access to hospitals so that they can provide personalized care to every patient.

One of the continued measuresbeing used at UCLA Hospital is the algorithm that helps determine patients that suffer from deteriorating health condition. Mahbouba believes that with the help of the platform, caregivers will be able to take precautions and know beforehand if the patient has a chance of suffering from conditions such as diabetes and heart disease. When implemented correctly, this will held decrease costs as well as prevent incidences where the patient needs to be admitted to a hospital or to visit the ER.

The goal is to answer the demand for predictive analysis using structured data including personal information and results from laboratory tests. There is also the possibility that, using systems provided by companies such as Rend Tech Associates, unstructured data can also be utilized. These are coming from sources that contain information such as ultrasound readings, generic tests and radiological scans.

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