Deadly flu is about to be defanged

What if we could predict and prevent a major pandemic outbreak?

What if we had the ability to process zettabytes of data to find the people most at risk of getting sick, and then quickly and precisely prevent illness from happening?

What if there are very specific areas of chronic disease treatment and management where they can all get the best care without the same medication regimen?

What if we could drastically reduce the time and cost of developing new drugs and bring them to market faster? What if all of this were possible today?

Now, it can be done.

The real impact of artificial intelligence today

In the vast world of big data, artificial intelligence plays a key role in all aspects of industry transformation, from manufacturing, transportation to retail, education, etc. All fields will benefit from the application of artificial intelligence. However, its application in the field of healthcare is more realistic because it is closely related to everyone's vital interests.

It is generally believed that applying artificial intelligence in the field of healthcare, allowing machines to diagnose diseases and prescribe medicines without the involvement of doctors, is like science fiction. Not only is it extremely unlikely, but there is not even a single successful case in the healthcare field so far.

Intel is working with partners across the healthcare industry to successfully deploy multiple AI solutions in various scenarios, from work offices to doctor's offices, from emergency rooms to living rooms, including:

Montefiore Health System : By using a common sense model to identify patients at risk for respiratory failure, medical staff can take timely action based on alarm prompts to save lives while conserving medical resources.

Stanford Medical : By using artificial intelligence to enhance the reconstruction of MRI images, the risk of intubation and sedation of pediatric patients during imaging examinations can be eliminated. A complete image that usually takes about an hour to complete now takes only about one minute.

Aikon Clinical Research : By using clinical data from sensors and wearable devices, it is possible to more quickly evaluate the effectiveness of new therapies in clinical trials without relying on cumbersome clinic visits and paper logs.

AccuHealth : Using home monitoring, data mining and predictive modeling, it is able to identify changes in the condition of patients with chronic diseases so that intervention can be made before the condition escalates or becomes acute.

Better health in the future

The application of artificial intelligence in the medical field is not necessarily successful. Currently, an average hospital generates 665 TB of data per year, but most of this data is useless. At least 80% of hospital data is unstructured, such as clinical notes, videos and images. Although electronic medical records (EMR) are a mandatory record system, they are not necessarily implemented. Only by using artificial intelligence can a comprehensive insight system be built using medical data.

Increasing the openness of data in the health system may help, and governments can play an active role in providing appropriate incentives and transparent regulation for sharing data. New technologies can also help.

For example, Intel researchers have made a significant breakthrough in practical methods for homomorphic encryption (a method that allows computer systems to perform computations on encrypted information without first decrypting it), which enables researchers to operate and process data in a more secure and private manner while also providing insightful analytical results.

In fact, there is still a lot of work to be done in the future, and Intel is uniquely positioned to help medical institutions succeed. Emerging healthcare data is massive, with more and more omics image data (i.e. genomics, proteomics), as well as large amounts of video data that require storage space and low-latency, high-reliability networks.

Intel has been investing in this envisioned system with its partners, building comprehensive infrastructure from data, storage to networks, and experimenting from edge to network to cloud, and everywhere in between. With hardware upgrades and optimizations for advanced deep learning frameworks, Intel® Xeon™ Scalable Processors have delivered 198 times better performance and 127 times better training performance than previous generations. Therefore, the Xeon platform is the core of many current AI platforms because it is well suited for industries like healthcare that require a lot of machine and deep learning applications.

However, hardware, storage and networking alone are not enough. It is also necessary to integrate the expertise of various data scientists, software developers, industry experts and ecosystem partners to solve the various problems faced by artificial intelligence in the healthcare industry end-to-end. In order to enrich and expand the professional knowledge and skills in the field of artificial intelligence, Intel launched the Intel AI Academy, which provides learning materials, community tools and technologies and is committed to promoting the development of artificial intelligence. Currently, more than 250,000 people participate in it every month.

In the future, Intel will continue to be committed to providing artificial intelligence solutions to solve various major challenges facing this era, including in the field of healthcare. Are you ready to look forward to more technological innovation?

* Recommended Reading * :

Click on the following mini program to enter the Intel micro site and view more exciting content!