With the expanding scale of the Internet, big data is changing the vast majority of industries or enterprises in this era, the medical industry is no exception, health care is becoming a key concern of people's attention to the issue of intelligence, digitalization as the characteristics of the medical information technology is flourishing, the medical industry, the type of data is also to the massive amount of data, complexity, variety of types of ways to change.
1. Electronic management of medical visit data
The collection of electronic medical records, including personal medical history, family medical history, allergies, and all medical test results. Shared in the information system, each doctor is able to add or change records in the system without having to go through time-consuming paper work. These records also help patients keep track of their medications and are an important data reference for medical research.
2. Health Prediction
Through data from wearable devices such as smartwatches, a health prediction model is built, and health data is continuously collected and stored in the cloud through these wearable devices to report on the patient's health status in real time. Applied to the prediction and analysis of millions of people and their various diseases, and in the future clinical trials will no longer be limited to small samples, but include everyone.
3. Medical Imaging and Clinical Diagnostics
By allowing big data robots to recognize and memorize all kinds of massive medical images, such as X-rays, MR*** vibration imaging, ultrasound ...... and other kinds of images. Deep mining and learning on a large number of medical records, training its diagnosis of the film, and ultimately realize to assist doctors in clinical decision-making, standardize the diagnosis and treatment path, and improve the efficiency of doctors.
4. Pharmaceutical R&D
Using big data for data modeling and analysis, predicting the clinical results of drugs can provide reference for the results of experiments in the clinical stage, saving time in the clinical stage and optimizing the results of clinical experiments. Pharmaceutical companies can also use data modeling and analytics to produce drugs with higher therapeutic success rates and dramatically shorten the time from development to market.